/Paper-Reading-ConvAI

πŸ“– Paper reading list in conversational AI (constantly updating πŸ€—).

Paper-Reading-ConvAI

Paper reading list in Conversational AI, mainly encompassing πŸ’¬ dialogue systems and πŸ“ natural language generation. This repository is constantly updating πŸ€— ...

Deep Learning in NLP

  • iNLP: "Interactive Natural Language Processing". arXiv(2023) [paper] ⭐⭐⭐⭐
  • Data Augmentation: "A Survey of Data Augmentation Approaches for NLP". ACL-Findings(2021) [paper]
  • Prompting: "Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing". arXiv(2021) [paper] ⭐⭐⭐⭐⭐
  • NLP World Scope: "Experience Grounds Language". EMNLP(2020) [paper] ⭐⭐⭐⭐⭐
  • Transformer-XL: "Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context". ACL(2019) [paper] [code]
  • Transformer: "Attention is All you Need". NeurIPS(2017) [paper] [code-official] [code-tf] [code-py] ⭐⭐⭐⭐⭐
  • VAE: "An Introduction to Variational Autoencoders". arXiv(2019) [paper]
  • Survey on Attention: "An Introductory Survey on Attention Mechanisms in NLP Problems". arXiv(2018) [paper] ⭐⭐⭐⭐⭐
  • Additive Attention: "Neural Machine Translation by Jointly Learning to Align and Translate". ICLR(2015) [paper]
  • Multiplicative Attention: "Effective Approaches to Attention-based Neural Machine Translation". EMNLP(2015) [paper]
  • Memory Net: "End-To-End Memory Networks". NeurIPS(2015) [paper]
  • Copy Mechanism (PGN): "Get To The Point: Summarization with Pointer-Generator Networks". ACL(2017) [paper] [code] ⭐⭐⭐⭐⭐
  • Copy Mechanism: "Incorporating Copying Mechanism in Sequence-to-Sequence Learning". ACL(2016) [paper]
  • ELMo: "Deep contextualized word representations". NAACL(2018) [paper] [code]
  • Glove: "GloVe: Global Vectors for Word Representation". EMNLP(2014) [paper] [code]
  • Word2Vec Tutorial: "word2vec Parameter Learning Explained". arXiv(2016) [paper] ⭐⭐⭐⭐⭐
  • Multi-task Learning: "An Overview of Multi-Task Learning in Deep Neural Networks". arXiv(2017) [paper]
  • Gradient Descent: "An Overview of Gradient Descent Optimization Algorithms". arXiv(2016) [paper] ⭐⭐⭐⭐⭐

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Dialogue Systems

Survey on Dialogue

  • Data Generation: "A Survey on Recent Advances in Conversational Data Generation". arXiv(2024) [paper]
  • Proactive Dialogue: "A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects". IJCAI(2023) [paper]
  • Responsible Dialogue: "Recent Advances towards Safe, Responsible, and Moral Dialogue Systems: A Survey". arXiv(2023) [paper]
  • Negotiation Dialogue: "Let's Negotiate! A Survey of Negotiation Dialogue Systems". arXiv(2022) [paper]
  • DL-based Dialogue: "Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey". arXiv(2021) [paper] ⭐⭐⭐⭐
  • Open-domain Dialogue: "Challenges in Building Intelligent Open-domain Dialog Systems". TOIS(2020) [paper]
  • Dialogue Systems: "A Survey on Dialogue Systems: Recent Advances and New Frontiers". SIGKDD Explorations(2017) [paper]
  • Dialogue Corpora: "A Survey of Available Corpora For Building Data-Driven Dialogue Systems". arXiv(2017) [paper] [data]

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Conversational LLMs

  • Parrot: "Parrot: Enhancing Multi-Turn Chat Models by Learning to Ask Questions". arXiv(2023) [paper]
  • MemoChat: "MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation". arXiv(2023) [paper]
  • Llama 2-Chat: "Llama 2: Open Foundation and Fine-Tuned Chat Models". Meta(2023) [paper] [code]
  • ChatGLM3: "ChatGLM3 Series: Open Bilingual Chat LLMs". Tsinghua(2023) [code]
  • ChatGLM2-6B: "ChatGLM2-6B: An Open Bilingual Chat LLM". Tsinghua(2023) [code]
  • MPC: "Prompted LLMs as Chatbot Modules for Long Open-domain Conversation". ACL-Findings(2023) [paper] [code]
  • MemoryBank-SiliconFriend: "MemoryBank: Enhancing Large Language Models with Long-Term Memory". arXiv(2023) [paper] [code]
  • UltraChat: "Enhancing Chat Language Models by Scaling High-quality Instructional Conversations". arXiv(2023) [paper] [data]
  • ChatAlpaca: "ChatAlpaca: A Multi-Turn Dialogue Corpus based on Alpaca Instructions". Github(2023) [data]
  • Phoenix: "Phoenix: Democratizing ChatGPT across Languages". arXiv(2023) [paper] [code]
  • Dolly: "Free Dolly: Introducing the World's First Truly Open Instruction-Tuned LLM". Databricks(2023) [code]
  • Baize: "Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data". arXiv(2023) [paper] [code]
  • Vicuna: "Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90% ChatGPT Quality". LMSYS Org(2023) [Blog] [code]
  • Koala: "Koala: A Dialogue Model for Academic Research". UC Berkeley(2023) [Blog] [code]
  • BELLE: "BELLE: Be Everyone's Large Language model Engine". LianjiaTech(2023) [code]
  • Alpaca: "Alpaca: A Strong, Replicable Instruction-Following Model". Stanford(2023) [Blog] [code] [alpaca-lora]
  • ChatGLM-6B: "An Open Bilingual Dialogue Language Model". Tsinghua(2023) [code]
  • Open-Assistant: "Open Assistant: Conversational AI for everyone". Github(2023) [project] [code]
  • ChatGPT: "ChatGPT: Optimizing Language Models for Dialogue". OpenAI(2022) [Blog] ⭐⭐⭐⭐⭐
  • Sparrow: "Improving alignment of dialogue agents via targeted human judgements". arXiv(2022) [paper] [data]
  • BlenderBot3: "BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage". arXiv(2022) [paper]
  • LaMDA: "LaMDA: Language Models for Dialog Applications". arXiv(2022) [paper]
  • GODEL: "GODEL: Large-Scale Pre-Training for Goal-Directed Dialog". arXiv(2022) [paper] [code]
  • Anthropic Assistant-v2: "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback". arXiv(2022) [paper]
  • Anthropic Assistant: "A General Language Assistant as a Laboratory for Alignment". arXiv(2021) [paper]

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Multimodal Dialogue

Situated and Embodied Dialogue

  • SLL: "Large Language Model based Situational Dialogues for Second Language Learning". arXiv(2024) [paper]
  • Emb-Plan: "Multimodal Embodied Plan Prediction Augmented with Synthetic Embodied Dialogue". EMNLP(2023) [paper]
  • WTaG: "Can Foundation Models Watch, Talk and Guide You Step by Step to Make a Cake?". EMNLP-Findings(2023) [paper] [code]
  • SIMMC-VR: "SIMMC-VR: A Task-oriented Multimodal Dialog Dataset with Situated and Immersive VR Streams". ACL(2023) [paper] ⭐⭐⭐⭐
  • SURE: "Multimodal Recommendation Dialog with Subjective Preference: A New Challenge and Benchmark". ACL(2023) [paper] [data]
  • SUGAR: "A Textual Dataset for Situated Proactive Response Selection". ACL(2023) [paper] [data]
  • MindDial: "MindDial: Belief Dynamics Tracking with Theory-of-Mind Modeling for Situated Neural Dialogue Generation". arXiv(2023) [paper]
  • HoloAssist: "HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World". ICCV(2023) [paper] [data] ⭐⭐⭐⭐
  • Collab: "Towards Collaborative Plan Acquisition through Theory of Mind Modeling in Situated Dialogue". IJCAI(2023) [paper] [code]
  • Alexa Arena: "Alexa Arena: A User-Centric Interactive Platform for Embodied AI". arXiv(2023) [paper] [code]
  • SEAGULL: "SEAGULL: An Embodied Agent for Instruction Following through Situated Dialog". Alexa Prize SimBot Challenge(2023) [paper]
  • SitCoM-DETR: "Which One Are You Referring To? Multimodal Object Identification in Situated Dialogue". EACL-SRW(2023) [paper] [code]
  • MLR: "Improving Situated Conversational Agents with Step-by-Step Multi-modal Logic Reasoning". DSTC11(2023) [paper]
  • SimpleMTOD: "SimpleMTOD: A Simple Language Model for Multimodal Task-Oriented Dialogue with Symbolic Scene Representation". arXiv(2023) [paper]
  • SPRING: "SPRING: Situated Conversation Agent Pretrained with Multimodal Questions from Incremental Layout Graph". AAAI(2023) [paper] [code]
  • DOROTHIE: "DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents". EMNLP-Findings(2022) [paper] [code] ⭐⭐⭐
  • LIGHT-curriculum: "Situated Dialogue Learning through Procedural Environment Generation". ACL(2022) [paper]
  • DANLI: "DANLI: Deliberative Agent for Following Natural Language Instructions". EMNLP(2022) [paper] [code]
  • PRS: "Learning to Mediate Disparities Towards Pragmatic Communication". ACL(2022) [paper] [code]
  • Joint-model: "Learning to Embed Multi-Modal Contexts for Situated Conversational Agents". NAACL-Findings(2022) [paper] [code]
  • TEACh_FILM: "Don't Copy the Teacher: Data and Model Challenges in Embodied Dialogue". EMNLP(2022) [paper] [code]
  • TEACh: "TEACh: Task-driven Embodied Agents that Chat". AAAI(2022) [paper] [data]
  • MindCraft: "MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks". EMNLP(2021) [paper] [code] ⭐⭐⭐
  • Multimodal-model: "Multimodal Interactions Using Pretrained Unimodal Models for SIMMC 2.0". DSTC10(2022) [paper] [code]
  • SIMMC 2.0: "SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations" EMNLP(2021) [paper] [code] ⭐⭐⭐⭐
  • MM-DST: "Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems". arXiv(2021) [paper]
  • SIMMC: "Situated and Interactive Multimodal Conversations". COLING(2020) [paper] [code]
  • Minecraft-BAP: "Learning to execute instructions in a Minecraft dialogue". ACL(2020) [paper] [code]
  • CerealBar: "Executing Instructions in Situated Collaborative Interactions". EMNLP(2019) [paper] [code]
  • Minecraft Dialogue: "Collaborative Dialogue in Minecraft". ACL(2019) [paper] [code]
  • CLG: "Collaborative Language Grounding Toward Situated Human‐Robot Dialogue". AI Magazine(2016) [paper] ⭐⭐⭐⭐
  • SHRD: "Back to the Blocks World: Learning New Actions through Situated Human-Robot Dialogue". SIGDIAL(2014) [paper]

Visually-grounded Dialogue

  • TIGER: "TIGER: A Unified Generative Model Framework for Multimodal Dialogue Response Generation". COLING(2024). [paper] [code]
  • DialogCC: "DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Dataset". NAACL(2024) [paper] [data]
  • VLAW-MDM: "A Framework for Vision-Language Warm-up Tasks in Multimodal Dialogue Models". EMNLP(2023) [paper] [code]
  • ZRIGF: "ZRIGF: An Innovative Multimodal Framework for Zero-Resource Image-Grounded Dialogue Generation". ACM MM(2023) [paper] [code]
  • VDialogUE: "VDialogUE: A Unified Evaluation Benchmark for Visually-grounded Dialogue". arXiv(2023) [paper]
  • TextBind: "TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild". arXiv(2023) [paper] [data]
  • VSTAR: "VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions". ACL(2023) [paper] [data]
  • ComSet: "Multimodal Persona Based Generation of Comic Dialogs". ACL(2023) [paper] [code]
  • MPCHAT: "MPCHAT: Towards Multimodal Persona-Grounded Conversation". ACL(2023) [paper] [code]
  • PaCE: "PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional Experts". ACL(2023) [paper] [code]
  • MMDialog: "MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation". ACL(2023) [paper] [data] ⭐⭐⭐
  • MDS-S2: "Dual Semantic Knowledge Composed Multimodal Dialog Systems". SIGIR(2023) [paper]
  • TikTalk: "TikTalk: A Multi-Modal Dialogue Dataset for Real-World Chitchat". arXiv(2023) [paper] [code]
  • CHAMPAGNE: "CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web Videos". arXiv(2023) [paper] [code]
  • MMChat: "MMChat: Multi-Modal Chat Dataset on Social Media". LREC(2022) [paper] [code]
  • CRVD: "Collaborative Reasoning on Multi-Modal Semantic Graphs for Video-Grounded Dialogue Generation". EMNLP-Findings(2022) [paper]
  • M3ED: "M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue Database". ACL(2022) [paper] [data]
  • MDRG: "Multimodal Dialogue Response Generation". ACL(2022) [paper]
  • UniTranSeR: "UniTranSeR: A Unified Transformer Semantic Representation Framework for Multimodal Task-Oriented Dialog System". ACL(2022) [paper]
  • PhotoChat: "PhotoChat: A Human-Human Dialogue Dataset With Photo Sharing Behavior For Joint Image-Text Modeling". ACL(2021) [paper] [data]
  • Multi-Modal Dialogue: "Constructing Multi-Modal Dialogue Dataset by Replacing Text with Semantically Relevant Images". ACL(2021) [paper] [code]
  • OpenViDial 2.0: "OpenViDial 2.0: A Larger-Scale, Open-Domain Dialogue Generation Dataset with Visual Contexts". arXiv(2021) [paper] [data]
  • TREASURE: "Multimodal Dialog System: Relational Graph-based Context-aware Question Understanding". ACM MM(2021) [paper] [code]
  • MMConv: "MMConv: An Environment for Multimodal Conversational Search across Multiple Domains". SIGIR(2021) [paper] [data]
  • Image Chat: "Image Chat: Engaging Grounded Conversations". ACL(2020) [paper] [data]
  • MTN: "Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems". ACL(2019) [paper] [code] ⭐⭐⭐
  • MELD: "MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations". ACL(2019) [paper] [data]
  • CLEVR-Dialog: "CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog". NAACL(2019) [paper] [data]
  • VisDial-RL: "Improving Generative Visual Dialog by Answering Diverse Questions". EMNLP(2019) [paper] [code]
  • MAGIC: "Multimodal Dialog System: Generating Responses via Adaptive Decoders". ACM MM(2019) [paper] [code]
  • KMD: "Knowledge-aware Multimodal Dialogue Systems". ACM MM(2018) [paper]
  • MMD: "Towards Building Large Scale Multimodal Domain-Aware Conversation Systems". AAAI(2018) [paper] [data]
  • Talk the Walk: "Talk the Walk: Navigating New York City through Grounded Dialogue". arXiv(2018) [paper] [code]
  • IGC: "Image-Grounded Conversations: Multimodal Context for Natural Question and Response Generation". IJCNLP(2017) [paper] [data]
  • VisDial: "Visual Dialog". CVPR(2017) [paper] [data]

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Proactive Dialogue

Misc. of Proactive Dialogue

  • DPDP: "Planning Like Human: A Dual-process Framework for Dialogue Planning". ACL(2024) [paper] [code]
  • PCA: "Towards Human-centered Proactive Conversational Agents". SIGIR(2024) [paper]
  • ProCoT: "Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration". EMNLP-Findings(2023) [paper] [code]
  • Tutorial: "Goal Awareness for Conversational AI: Proactivity, Non-collaborativity, and Beyond". ACL(2023) [paper]

Target-oriented Dialogue

  • PAI: "Towards Goal-oriented Intelligent Tutoring Systems in Online Education". arXiv(2023) [paper]
  • TopDial: "Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation". EMNLP(2023) [paper] [code]
  • RTCP: "Reinforced Target-driven Conversational Promotion". EMNLP(2023) [paper] [code]
  • MTGP: "MTGP: Multi-turn Target-oriented Dialogue Guided by Generative Global Path with Flexible Turns". ACL-Findings(2023) [paper] [code]
  • COLOR: "Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue". ACL-Findings(2023) [paper] [code] ⭐⭐⭐
  • TopKG: "TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph". COLING(2022) [paper] [code]
  • TGCP: "Target-Guided Open-Domain Conversation Planning". COLING(2022) [paper] [code]
  • FOP: "Long-term Control for Dialogue Generation: Methods and Evaluation". NAACL(2022) [paper] [code]
  • CODA: "Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation". NAACL-Findings(2022) [paper] [code]
  • OTTers: "OTTers: One-turn Topic Transitions for Open-Domain Dialogue". ACL(2021) [paper] [data]
  • CG-nAR: "Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systems". EMNLP(2021) [paper] [code] ⭐⭐⭐
  • DuConv: "Proactive Human-Machine Conversation with Explicit Conversation Goals". ACL(2019) [paper] [code]
  • CKC: "Keyword-Guided Neural Conversational Model". AAAI(2021) [paper] [code]
  • KnowHRL: "Knowledge Graph Grounded Goal Planning for Open-Domain Conversation Generation". AAAI(2020) [paper]
  • DKRN: "Dynamic Knowledge Routing Network For Target-Guided Open-Domain Conversation". AAAI(2020) [paper] [code]
  • TGConv: "Target-Guided Open-Domain Conversation". ACL(2019) [paper] [code]

Non-collaborative Dialogue (Persuasion and Negotiation)

  • TRIP: "Strength Lies in Differences! Towards Effective Non-collaborative Dialogues via Tailored Strategy Planning". arXiv(2024) [paper]
  • INA: "INA: An Integrative Approach for Enhancing Negotiation Strategies with Reward-Based Dialogue System". EMNLP(2023) [paper] [data]
  • I-Pro: "Interacting with Non-Cooperative User: A New Paradigm for Proactive Dialogue Policy". SIGIR(2022) [paper]
  • PAAD: "Towards a Progression-Aware Autonomous Dialogue Agent". NAACL(2022) [paper] [code] ⭐⭐⭐
  • PersRFI: "Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration". EMNLP-Findings(2021) [paper] [code]
  • ResPer: "RESPER: Computationally Modelling Resisting Strategies in Persuasive Conversations". EACL(2021) [paper] [code]
  • ARDM: "Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models". EACL(2021) [paper] [code]
  • DialoGraph: "DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues". ICLR(2021) [paper] [code] ⭐⭐⭐
  • NegotiationToM: "Improving Dialog Systems for Negotiation with Personality Modeling". ACL(2021) [paper] [code]
  • FeHED: "Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History". ICLR(2020) [paper] [code]
  • CTX-PSA: "Learning to Plan and Realize Separately for Open-Ended Dialogue Systems". EMNLP-Findings(2020) [paper] [code]
  • Negotiation-Coach: "A Dynamic Strategy Coach for Effective Negotiation". SIGDIAL(2019) [paper] [code]
  • PersuasionForGood: "Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good". ACL(2019) [paper] [data]
  • CraigslistBargain: "Decoupling Strategy and Generation in Negotiation Dialogues". EMNLP(2018) [paper] [data]

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Personalized Dialogue

Character-based Dialogue

  • LLM-Werewolf: "Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf". arXiv(2023) [paper]
  • ChatHaruhi: "ChatHaruhi: Reviving Anime Character in Reality via Large Language Model". arXiv(2023) [report] [code]
  • DPCD: "Hi Sheldon! Creating Deep Personalized Characters from TV Shows". arXiv(2023) [paper] [data]
  • Cornell-Rich: "Personalised Language Modelling of Screen Characters Using Rich Metadata Annotations". arXiv(2023) [paper] [data]
  • KNUDGE: "Ontologically Faithful Generation of Non-Player Character Dialogues". arXic(2022) [paper]
  • HPD: "Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters". arXiv(2022) [paper] [data]
  • DialStory: "A Benchmark for Understanding and Generating Dialogue between Characters in Stories". arXiv(2022) [paper]
  • CareCall: "Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Models". NAACL(2022) [paper] [data]
  • PDP: "Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances". NAACL(2022) [paper] [code]
  • RPA: "Am I Me or You? State-of-the-Art Dialogue Models Cannot Maintain an Identity". NAACL-Findings(2022) [paper]
  • CharacterChat: "CharacterChat: Supporting the Creation of Fictional Characters through Conversation and Progressive Manifestation with a Chatbot". ACM C&C(2021οΌ‰[paper]
  • ALOHA: "ALOHA: Artificial Learning of Human Attributes for Dialogue Agents". AAAI(2020) [paper] [code]
  • LIGHT: "Learning to Speak and Act in a Fantasy Text Adventure Game". EMNLP(2019) [paper] [data] ⭐⭐⭐

Personality-aware Dialogue

  • UBPL: "Tailoring Personality Traits in Large Language Models via Unsupervisedly-Built Personalized Lexicons". arXiv(2023) [paper]
  • CharacterChat: "CharacterChat: Learning towards Conversational AI with Personalized Social Support". arXiv(2023) [paper] [code]
  • ChatGPT-MBTI: "Can ChatGPT Assess Human Personalities? A General Evaluation Framework". arXiv(2023) [paper] [code]
  • Prompted Personality: "Controlling Personality Style in Dialogue with Zero-Shot Prompt-Based Learning". IWSDS(2023) [paper]
  • CPED: "CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI". arXiv(2022) [paper] [data] ⭐⭐⭐
  • PELD: "Automatically Select Emotion for Response via Personality-affected Emotion Transition". ACL-Findings(2021) [paper] [data]
  • FriendsPersona: "Automatic Text-based Personality Recognition on Monologues and Multiparty Dialogues Using Attentive Networks and Contextual Embeddings". AAAI-Student Abstract(2020) [paper] [data]
  • APR: "Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue". INTERSPEECH(2019) [paper]
  • PersonalDilaog: "Personalized Dialogue Generation with Diversified Traits". arXiv(2019) [paper] [data]
  • PersonageNLG: "Controlling Personality-Based Stylistic Variation with Neural Natural Language Generators". SIGDIAL(2018) [paper] [data]

Persona-based Dialogue

  • ComperDial: "ComperDial: Commonsense Persona-grounded Dialogue Dataset and Benchmark". arXiv(2024) [paper]
  • IDL: ""In Dialogues We Learn": Towards Personalized Dialogue Without Pre-defined Profiles through In-Dialogue Learning". arXiv(2024) [paper]
  • DialogICL: "Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation". arXiv(2024) [paper]
  • VaRMI: "Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning". EMNLP(2023) [paper] [code]
  • OPELA: "When Crowd Meets Persona: Creating a Large-Scale Open-Domain Persona Dialogue Corpus". arXiv(2023) [paper] [data]
  • ORIG: "Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization". ACL-Findings(2023) [paper] [code]
  • CLV: "Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona". ACL(2023) [paper] [code]
  • SimOAP: "SimOAP: Improve Coherence and Consistency in Persona-based Dialogue Generation via Over-sampling and Post-evaluation". ACL(2023) [paper] [code]
  • LMEDR: "Learning to Memorize Entailment and Discourse Relations for Persona-Consistent Dialogues". AAAI(2023) [paper] [code]
  • Retrieval-to-Prediction: "Improving Personality Consistency in Conversation by Persona Extending". CIKM(2022) [paper] [code]
  • Implicit-Persona: "A Personalized Dialogue Generator with Implicit User Persona Detection". COLING(2022) [paper]
  • CareCallMemory: "Keep Me Updated! Memory Management in Long-term Conversations". EMNLP-Findings(2022) [paper] [data]
  • PersonaDefense: "You Don't Know My Favorite Color: Preventing Dialogue Representations from Revealing Speakers' Private Personas". NAACL(2022) [paper] [code]
  • Prompt-Tuning: "Building a Personalized Dialogue System with Prompt-Tuning". NAACL-SRW(2022) [paper]
  • DuLeMon: "Long Time No See! Open-Domain Conversation with Long-Term Persona Memory". ACL-Findings(2022) [paper] [data] ⭐⭐⭐
  • INFO: "You Truly Understand What I Need: Intellectual and Friendly Dialogue Agents grounding Knowledge and Persona". EMNLP-Findings(2022) [paper] [code]
  • FoCus: "Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledge". AAAI(2022) [paper] [code] ⭐⭐⭐
  • MSP: "Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generation". NAACL(2022) [paper]
  • GME: "Transferable Persona-Grounded Dialogues via Grounded Minimal Edits". EMNLP(2021) [paper] [code]
  • BoB: "BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data". ACL(2021) [paper] [code]
  • PABST: "Unsupervised Enrichment of Persona-grounded Dialog with Background Stories". ACL(2021) [paper] [code]
  • DHAP: "One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles". SIGIR(2021) [paper]
  • Pchatbot: "Pchatbot: A Large-Scale Dataset for Personalized Chatbot". SIGIR(2021) [paper] [data] ⭐⭐⭐
  • COMPAC: "Like hiking? You probably enjoy nature: Persona-grounded Dialog with Commonsense Expansions". EMNLP(2020) [paper] [code]
  • pragmatic-consistency: "Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness". EMNLP(2020) [paper] [code] ⭐⭐⭐⭐
  • XPersona: "XPersona: Evaluating Multilingual Personalized Chatbot". arXiv(2020) [paper] [data]
  • KvPI: "Profile Consistency Identification for Open-domain Dialogue Agents". EMNLP(2020) [paper] [code]
  • GDR: "Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation". ACL(2020) [paper]
  • P^2Bot: "You Impress Me: Dialogue Generation via Mutual Persona Perception". ACL(2020) [paper] [code]
  • RCDG: "Generating Persona Consistent Dialogues by Exploiting Natural Language Inference". AAAI(2020) [paper] [code]
  • Persona-sparse: "A Pre-training Based Personalized Dialogue Generation Model with Persona-sparse Data". AAAI(2020) [paper]
  • PersonaWAE: "Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders". EMNLP(2019) [paper]
  • PAML: "Personalizing Dialogue Agents via Meta-Learning". ACL(2019) [paper] [code]
  • PersonaChat: "Personalizing Dialogue Agents: I have a dog, do you have pets too?" ACL(2018) [paper] [data] ⭐⭐⭐
  • PCCM: "Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation". IJCAI(2018) [paper]

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Emotional Dialogue

Emotional Support Dialogue

  • Preference Bias: "Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation". ACL(2024) [paper]
  • ESCoT: "ESCoT: Towards Interpretable Emotional Support Dialogue Systems". ACL(2024) [paper] [code]
  • Muffin: "Muffin: Mitigating Unhelpfulness in Emotional Support Conversations with Multifaceted AI Feedback". ACL-Findings(2024) [paper] [code]
  • DDRCU: "Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation". SIGIR(2024) [paper] [code]
  • KEMI: "Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations". ACL(2023) [paper] [code] ⭐⭐⭐⭐
  • CSConv: "A Cognitive Stimulation Dialogue System with Multi-source Knowledge Fusion for Elders with Cognitive Impairment". ACL(2023) [paper] [code]
  • AugESC: "AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation". ACL-Findings(2023) [paper]
  • TransESC: "TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition". ACL-Findings(2023) [paper] [code]
  • PAL: "PAL: Persona-Augmented Emotional Support Conversation Generation". ACL-Findings(2023) [paper] [code]
  • MultiESC: "Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning". EMNLP(2022) [paper] [code] ⭐⭐⭐⭐
  • MISC: "MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation". ACL(2022) [paper] [code]
  • C3KG: "C3KG: A Chinese Commonsense Conversation Knowledge Graph". ACL-Findings(2022) [paper] [data]
  • GLHG: "Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation". IJCAI(2022) [paper]
  • ESConv: "Towards Emotional Support Dialog Systems". ACL(2021) [paper] [data] ⭐⭐⭐⭐

Empathetic Dialogue

  • STICKERCONV: "STICKERCONV: Generating Multimodal Empathetic Responses from Scratch". ACL(2024) [paper] [data]
  • PerceptiveAgent: "Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction". ACL(2024) [paper] [code]
  • E-CORE: "E-CORE: Emotion Correlation Enhanced Empathetic Dialogue Generation" EMNLP(2023) [paper]
  • EmpSOA: "Don't Lose Yourself! Empathetic Response Generation via Explicit Self-Other Awareness". ACL-Findings(2023) [paper] [code]
  • CASE: "CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation". ACL(2023) [paper] [code]
  • CARE: "CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation". EMNLP-Findings(2022) [paper] [code]
  • EmpGPT-3: "Does GPT-3 Generate Empathetic Dialogues? A Novel In-Context Example Selection Method and Automatic Evaluation Metric for Empathetic Dialogue Generation". COLING(2022) [paper] [code]
  • PosEmoDial: "Towards Multi-Turn Empathetic Dialogs with Positive Emotion Elicitation". arXiV(2022) [paper]
  • CEM: "CEM: Commonsense-aware Empathetic Response Generation". AAAI(2022) [paper] [code]
  • GEE: "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes". EMNLP(2021) [paper] [code]
  • RecEC: "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations". EMNLP-Findings(2021) [paper] [code]
  • CoMAE: "CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation". ACL-Findings(2021) [paper] [code]
  • CARE: "CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts". AAAI(2021) [paper] [code]
  • EmpDG: "EmpDG: Multi-resolution Interactive Empathetic Dialogue Generation". COLING(2020) [paper] [code]
  • MIME: "MIME: MIMicking Emotions for Empathetic Response Generation". EMNLP(2020) [paper] [code]
  • PEC: "Towards Persona-Based Empathetic Conversational Models". EMNLP(2020) [paper] [code]
  • MoEL: "MoEL: Mixture of Empathetic Listeners". EMNLP(2019) [paper] [code]
  • EmpatheticDialogues: "Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset". ACL(2019) [paper] [data] ⭐⭐⭐
  • EmoDS: "Generating Responses with a Specific Emotion in Dialog". ACL(2019) [paper]
  • MojiTalk: "MojiTalk: Generating Emotional Responses at Scale". ACL(2018) [paper]
  • ECM: "Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory". AAAI(2018) [paper] [code]

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Recommendation Dialogue and CRS

  • TCP-Dial: "Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems". arXiv(2022) [paper] [code]
  • KERS: "KERS: A Knowledge-Enhanced Framework for Recommendation Dialog Systems with Multiple Subgoals". EMNLP-Findings(2021) [paper] [code]
  • DuRecDial2.0: "DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation". EMNLP(2021) [paper] [code]
  • DuRecDial: "Towards Conversational Recommendation over Multi-Type Dialogs". ACL(2020) [paper] [code] ⭐⭐⭐⭐
  • TG-ReDial: "Towards Topic-Guided Conversational Recommender System". COLING(2020) [paper] [code]
  • INSPIRED: "INSPIRED: Toward Sociable Recommendation Dialog Systems". EMNLP(2020) [paper] [data]
  • GoRecDial: "Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue". EMNLP(2019) [paper] [code]
  • CRS-Survey: "A Survey on Conversational Recommender Systems". ACM Computing Surveys(2021) [paper]
  • CRS-Survey: "Advances and Challenges in Conversational Recommender Systems: A Survey ". arXiv(2021) [paper]
  • CRSLab: "CRSLab: An Open-Source Toolkit for Building Conversational Recommender System". arXiv(2021) [paper] [code] ⭐⭐⭐
  • MESE: "Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Information". NAACL(2022) [paper] [code]
  • C2-CRS: "C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System". WSDM(2022) [paper] [code]
  • BotPlay: "Self-Supervised Bot Play for Conversational Recommendation with Justifications". arXiv(2021) [paper]
  • RID: "Finetuning Large-Scale Pre-trained Language Models for Conversational Recommendation with Knowledge Graph". arXiv(2021) [paper] [code]
  • CRFR: "CRFR: Improving Conversational Recommender Systems via Flexible Fragments Reasoning on Knowledge Graphs". EMNLP(2021) [paper]
  • NTRD: "Learning Neural Templates for Recommender Dialogue System". EMNLP(2021) [paper] [code]
  • CR-Walker: "CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation". EMNLP(2021) [paper] [code] ⭐⭐⭐⭐
  • RevCore: "RevCore: Review-augmented Conversational Recommendation". ACL-Findings(2021) [paper] [code]
  • KECRS: "KECRS: Towards Knowledge-Enriched Conversational Recommendation System". arXiv(2021) [paper]
  • FPAN: "Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation". WSDM(2021) [paper] [code]
  • UNICORN: "Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning". SIGIR(2021) [paper] [code]
  • KGSF: "Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion". KDD(2020) [paper] [code]
  • CPR: "Interactive Path Reasoning on Graph for Conversational Recommendation". KDD(2020) [paper] [code]
  • EAR: "Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems". WSDM(2020) [paper] [code]
  • KBRD: "Towards Knowledge-Based Recommender Dialog System". EMNLP(2019) [paper] [code]
  • ReDial: "Towards Deep Conversational Recommendations". NeurIPS(2018) [paper] [data]

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Knowledge-grounded Dialogue

  • DOCTOR: "Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents". EMNLP(2023) [paper] [code] [demo] ⭐⭐⭐⭐
  • GATE: "Well Begun is Half Done: Generator-agnostic Knowledge Pre-Selection for Knowledge-Grounded Dialogue". EMNLP(2023) [paper] [code]
  • CONNER: "Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators". EMNLP(2023) [paper] [code]
  • K-DIAL: "Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment". EMNLP-Findings(2023) [paper]
  • GLM-Dialog: "GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation". arXiv(2023) [paper] [code]
  • RHO: "RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding". ACL-Findings(2023) [paper] [code]
  • MultiRefKGC: "There Is No Standard Answer: Knowledge-Grounded Dialogue Generation with Adversarial Activated Multi-Reference Learning". EMNLP(2022) [paper] [code] ⭐⭐⭐
  • CorefDiffs: "CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations". COLING(2022) [paper] [code]
  • DTR: "Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting". NAACL(2022) [paper] [code]
  • XDAI: "XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation". KDD(2022) [paper] [code]
  • PersonaKGC: "There Are a Thousand Hamlets in a Thousand People's Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory". ACL(2022) [paper] [code]
  • KI: "Lexical Knowledge Internalization for Neural Dialog Generation". ACL(2022) [paper] [code]
  • DiffKG: "Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems". ACL-Findings(2022) [paper] [code] ⭐⭐⭐
  • KSAM: "KSAM: Infusing Multi-Source Knowledge into Dialogue Generation via Knowledge Source Aware Multi-Head Decoding". ACL-Findings(2022) [paper]
  • MDSP: "Multi-Stage Prompting for Knowledgeable Dialogue Generation". ACL-Findings(2022) [paper] [code]
  • FSB: "Few-Shot Bot: Prompt-Based Learning for Dialogue Systems". arXiv(2021) [paper] [code] ⭐⭐⭐
  • P-GDG: "Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation". arXiv(2021) [paper]
  • KAT-TSLF: "A Three-Stage Learning Framework for Low-Resource Knowledge-Grounded Dialogue Generation". EMNLP(2021) [paper] [code]
  • DIALKI: "DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization". EMNLP(2021) [paper] [code]
  • CoLV: "CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation". EMNLP(2021) [paper]
  • SKT-KG: "Augmenting Knowledge-grounded Conversations with Sequential Knowledge Transition". NAACL(2021) [paper]
  • MSKE: "More is Better: Enhancing Open-Domain Dialogue Generation via Multi-Source Heterogeneous Knowledge". EMNLP(2021) [paper] [code]
  • EARL: "EARL: Informative Knowledge-Grounded Conversation Generation with Entity-Agnostic Representation Learning". EMNLP(2021) [paper] [code]
  • KGD-CF: "Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features". ACL(2021) [paper]
  • SECE: "Space Efficient Context Encoding for Non-Task-Oriented Dialogue Generation with Graph Attention Transformer". ACL(2021) [paper] [code] ⭐⭐⭐
  • MIKe: "Initiative-Aware Self-Supervised Learning for Knowledge-Grounded Conversations". SIGIR(2021) [paper] [code]
  • GOKC: "Learning to Copy Coherent Knowledge for Response Generation". AAAI(2021) [paper] [code]
  • KnowledGPT: "Knowledge-Grounded Dialogue Generation with Pre-trained Language Models". EMNLP(2020) [paper] [code]
  • DiffKS: "Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation". EMNLP-Findings(2020) [paper] [code]
  • DukeNet: "DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation". SIGIR(2020) [paper] [code]
  • CCN: "Cross Copy Network for Dialogue Generation". EMNLP(2020) [paper] [code]
  • PIPM: "Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation". EMNLP(2020) [paper]
  • ConceptFlow: "Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs". ACL(2020) [paper] [code] ⭐⭐⭐⭐
  • ConKADI: "Diverse and Informative Dialogue Generation with Context-Specific Commonsense Knowledge Awareness". ACL(2020) [paper] [code] ⭐⭐⭐
  • KIC: "Generating Informative Conversational Response using Recurrent Knowledge-Interaction and Knowledge-Copy". ACL(2020) [paper]
  • SKT: "Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue". ICLR(2020) [paper] [code] ⭐⭐⭐
  • KdConv: "KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation". ACL(2020) [paper] [data]
  • TransDG: "Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering". AAAI(2020) [paper] [code]
  • RefNet: "RefNet: A Reference-aware Network for Background Based Conversation". AAAI(2020) [paper] [code]
  • GLKS: "Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation". AAAI(2020) [paper] [code]
  • AKGCM: "Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs". EMNLP(2019) [paper] [code]
  • DyKgChat: "DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs". EMNLP(2019) [paper] [code]
  • OpenDialKG: "OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs". ACL(2019) [paper] [data]
  • WoW: "Wizard of Wikipedia: Knowledge-Powered Conversational agents". ICLR(2019) [paper]
  • PostKS: "Learning to Select Knowledge for Response Generation in Dialog Systems". IJCAI(2019) [paper] [code-1] [code-2] ⭐⭐⭐
  • NKD: "Knowledge Diffusion for Neural Dialogue Generation". ACL(2018) [paper] [data]
  • Dual Fusion: "Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm". IJCAI(2018) [paper]
  • CCM: "Commonsense Knowledge Aware Conversation Generation with Graph Attention". IJCAI(2018) [paper] [code-tf] [code-py] ⭐⭐⭐⭐⭐
  • MTask: "A Knowledge-Grounded Neural Conversation Model". AAAI(2018) [paper]
  • GenDS: "Flexible End-to-End Dialogue System for Knowledge Grounded Conversation". arXiv(2017) [paper]

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Task-oriented Dialogue

  • P-ToD: "Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward Function". CIKM(2022) [paper]
  • Dialogic: "Dialogic: Controllable Dialogue Simulation with In-Context Learning". EMNLP-Findings(2022) [paper] [code] ⭐⭐⭐
  • KB-Adapter: "Injecting Domain Knowledge in Language Models for Task-Oriented Dialogue Systems". EMNLP(2022) [paper] [code]
  • TacoBot: "Bootstrapping a User-Centered Task-Oriented Dialogue System". Proceedings of Alexa Prize TaskBot(2021) [paper] ⭐⭐⭐
  • USDA: "User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems". WWW(2022) [paper] [code]
  • USS: "Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue Systems". SIGIR(2021) [paper] [data]
  • NS-Dial: "An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation". ACL(2022) [paper] [code]
  • GALAXY: "GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection". AAAI(2022) [paper] [code]
  • PPTOD: "Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System". arXiv(2021) [paper] [code]
  • ToDCL: "Continual Learning in Task-Oriented Dialogue Systems". EMNLP(2021) [paper] [code]
  • IR-Net: "Intention Reasoning Network for Multi-Domain End-to-end Task-Oriented Dialogue". EMNLP(2021) [paper]
  • HyKnow: "HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management". ACL-Findings(2021) [paper] [code]
  • DDMN: "Dual Dynamic Memory Network for End-to-End Multi-turn Task-oriented Dialog Systems". COLING(2020) [paper] [code] ⭐⭐⭐
  • ToD-BERT: "ToD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogues". EMNLP(2020) [paper] [code]
  • GraphDialog: "GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems". EMNLP(2020) [paper] [code]
  • MARCO: "Multi-Domain Dialogue Acts and Response Co-Generation". ACL(2020) [paper] [code]
  • DF-Net: "Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog". ACL(2020) [paper] [code]
  • MALA: "MALA: Cross-Domain Dialogue Generation with Action Learning". AAAI(2020) [paper]
  • SGD: "Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset". AAAI(2020) [paper] [data]
  • CrossWOZ: "CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset". TACL(2020) [paper] [code]
  • MultiWOZ: "MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling". EMNLP(2018) [paper] [code]
  • Neural Task-Oriented Dialogue: "Learning to Memorize in Neural Task-Oriented Dialogue Systems". MPhil Thesis(2019) [paper] ⭐⭐⭐⭐
  • GLMP: "Global-to-local Memory Pointer Networks for Task-Oriented Dialogue". ICLR(2019) [paper] [code] ⭐⭐⭐⭐⭐
  • KB Retriever: "Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever". EMNLP(2019) [paper] [data]
  • TRADE: "Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems". ACL(2019) [paper] [code]
  • WMM2Seq: "A Working Memory Model for Task-oriented Dialog Response Generation". ACL(2019) [paper]
  • Pretrain-Fine-tune: "Training Neural Response Selection for Task-Oriented Dialogue Systems". ACL(2019) [paper] [data]
  • Multi-level Mem: "Multi-Level Memory for Task Oriented Dialogs". NAACL(2019) [paper] [code] ⭐⭐⭐
  • BossNet: "Disentangling Language and Knowledge in Task-Oriented Dialogs ". NAACL(2019) [paper] [code]
  • SDN: "Subgoal Discovery for Hierarchical Dialogue Policy Learning". EMNLP(2018) [paper] ⭐⭐⭐
  • D3Q: "Discriminative Deep Dyna-Q: Robust Planning for Dialogue Policy Learning". EMNLP(2018) [paper] [code]
  • DDQ: "Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning". ACL(2018) [paper] [code]
  • MAD: "Memory-augmented Dialogue Management for Task-oriented Dialogue Systems". TOIS(2018) [paper]
  • TSCP: "Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures". ACL(2018) [paper] [code]
  • Mem2Seq: "Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems". ACL(2018) [paper] [code] ⭐⭐⭐⭐
  • Topic-Seg-Label: "A Weakly Supervised Method for Topic Segmentation and Labeling in Goal-oriented Dialogues via Reinforcement Learning". IJCAI(2018) [paper] [code]
  • AliMe: "AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine". ACL(2017) [paper]
  • KVR Net: "Key-Value Retrieval Networks for Task-Oriented Dialogue". SIGDIAL(2017) [paper] [data]

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Open-domain Dialogue

Long-term Dialogue

  • THEANINE: "THEANINE: Revisiting Memory Management in Long-term Conversations with Timeline-augmented Response Generation". arXiv(2024) [paper]
  • LD-Agent: "Hello Again! LLM-powered Personalized Agent for Long-term Dialogue". arXiv(2024) [paper] [code]
  • CPD: "Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue". IJCAI(2024) [paper]
  • TemporalMemory: "Toward Conversational Agents with Context and Time Sensitive Long-term Memory". arXiv(2024) [paper] [data]
  • LoCoMo: "Evaluating Very Long-Term Conversational Memory of LLM Agents". ACL(2024) [paper] [data] ⭐⭐⭐
  • Conversation Chronicles: "Conversation Chronicles: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversations". EMNLP(2023) [paper] [data]
  • GapChat: "Mind the Gap Between Conversations for Improved Long-Term Dialogue Generation". EMNLP-Findings(2023) [paper] [data]
  • UniMC: "UniMC: A Unified Framework for Long-Term Memory Conversation via Relevance Representation Learning". arXiv(2023) [paper]
  • RS: "Recursively Summarizing Enables Long-Term Dialogue Memory in Large Language Models". arXiv(2023) [paper]
  • MSC: "Beyond Goldfish Memory: Long-Term Open-Domain Conversation". ACL(2022) [paper] [data] ⭐⭐⭐

Response Generation

  • Overview: "Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next". ACL-NLP4ConvAI(2022) [paper] ⭐⭐⭐
  • Chirpy Cardinal: "Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent". SIGDIAL(2022) [paper] [code] [project]
  • TIL: "Towards Efficient Dialogue Pre-training with Transferable and Interpretable Latent Structure". EMNLP(2022) [paper]
  • ProphetChat: "ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation". ACL(2022) [paper]
  • DialoFlow: "Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances". ACL(2021) [paper] [code]
  • DiSCoL: "DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation". NAACL(2021) [paper] [code]
  • DialogBERT: "DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances". AAAI(2021) [paper]
  • BlenderBot: "Recipes for Building an Open-Domain Chatbot". EACL(2021) [paper] [code]
  • CDial-GPT: "A Large-Scale Chinese Short-Text Conversation Dataset". NLPCC(2020) [paper] [code]
  • DialoGPT: "DialoGPT : Large-Scale Generative Pre-training for Conversational Response Generation". ACL(2020) [paper] [code] ⭐⭐⭐⭐
  • CG-Policy: "Conversational Graph Grounded Policy Learning for Open-Domain Conversation Generation". ACL(2020) [paper]
  • PLATO-XL: "PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation". arXiv(2021) [paper] [code]
  • PLATO-2: "PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning". ACL-Findings(2021) [paper] [code]
  • PLATO: "PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable". ACL(2020) [paper] [code]
  • Guyu: "An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue Generation". arXiv(2020) [paper] [code]
  • CL4Dialogue: "Group-wise Contrastive Learning for Neural Dialogue Generation". EMNLP-Findings(2020) [paper] [code] ⭐⭐⭐
  • Neg-train: "Negative Training for Neural Dialogue Response Generation". ACL(2020) [paper] [code]
  • HDSA: "Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention". ACL(2019) [paper] [code] ⭐⭐⭐
  • CAS: "Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory". NAACL(2019) [paper] [code]
  • Edit-N-Rerank: "Response Generation by Context-aware Prototype Editing". AAAI(2019) [paper] [code] ⭐⭐⭐
  • HVMN: "Hierarchical Variational Memory Network for Dialogue Generation". WWW(2018) [paper] [code]
  • XiaoIce: "The Design and Implementation of XiaoIce, an Empathetic Social Chatbot". arXiv(2018) [paper] ⭐⭐⭐
  • D2A: "Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base". NeurIPS(2018) [paper] [code]
  • DAIM: "Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization". NeurIPS(2018) [paper]
  • REASON: "Dialog Generation Using Multi-turn Reasoning Neural Networks". NAACL(2018) [paper]
  • STD/HTD: "Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders". ACL(2018) [paper] [code]
  • CSF: "Generating Informative Responses with Controlled Sentence Function". ACL(2018) [paper] [code]
  • DAWnet: "Chat More: Deepening and Widening the Chatting Topic via A Deep Model". SIGIR(2018) [paper] [code]
  • ZSDG: "Zero-Shot Dialog Generation with Cross-Domain Latent Actions". SIGDIAL(2018) [paper] [code]
  • DUA: "Modeling Multi-turn Conversation with Deep Utterance Aggregation". COLING(2018) [paper] [code]
  • Data-Aug: "Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding". COLING(2018) [paper] [code]
  • DC-MMI: "Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints". EMNLP(2018) [paper] [code]
  • cVAE-XGate/CGate: "Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity". EMNLP(2018) [paper] [code]
  • Retrieval+multi-seq2seq: "An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems". IJCAI(2018) [paper]
  • DAM: "Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network". ACL(2018) [paper] [code] ⭐⭐⭐⭐
  • SMN: "Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots". ACL(2017) [paper] [code] ⭐⭐⭐
  • CVAE/KgCVAE: "Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders". ACL(2017) [paper] [code] ⭐⭐⭐
  • TA-Seq2Seq: "Topic Aware Neural Response Generation". AAAI(2017) [paper] [code]
  • MA: "Mechanism-Aware Neural Machine for Dialogue Response Generation". AAAI(2017) [paper]
  • VHRED: "A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues". AAAI(2017) [paper] [code]
  • HRED: "Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models". AAAI(2016) [paper] [code]
  • RL-Dialogue: "Deep Reinforcement Learning for Dialogue Generation". EMNLP(2016) [paper]
  • MMI: "A Diversity-Promoting Objective Function for Neural Conversation Models". NAACL(2016) [paper] [code]

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Dialogue Evaluation

  • DialogBench: "DialogBench: Evaluating LLMs as Human-like Dialogue Systems". NAACL(2024) [paper] [code]
  • ChatEval: "ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate". arXiv(2023) [paper] [code]
  • ACCENT: "ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems". ACL(2023) [paper] [code]
  • LLMEval: "Understanding the Effectiveness of Very Large Language Models on Dialog Evaluation". IWSDS(2023) [paper]
  • ChatEvalPlatform: "Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems". arXiv(2022) [paper] [code]
  • MDD-Eval: "MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation". AAAI(2022) [paper] [code]
  • Self-Eval: "SelF-Eval: Self-supervised Fine-grained Dialogue Evaluation". COLING(2022) [paper] [code]
  • FineD-Eval: "FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation". EMNLP(2022) [paper] [code]
  • FlowEval: "FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows". EMNLP(2022) [paper]
  • IM2: "IM^2: an Interpretable and Multi-category Integrated Metric Framework for Automatic Dialogue Evaluation". EMNLP(2022) [paper] [code]
  • Q^2: "$Q^{2}$: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering". EMNLP(2021) [paper] [code]
  • QuantiDCE: "Towards Quantifiable Dialogue Coherence Evaluation". ACL(2021) [paper] [code]
  • DynaEval: "DynaEval: Unifying Turn and Dialogue Level Evaluation". ACL(2021) [paper] [code]
  • Review: "How to Evaluate Your Dialogue Models: A Review of Approaches". arXiv(2021) [paper]
  • ConvLabEval: "Is Your Goal-Oriented Dialog Model Performing Really Well? Empirical Analysis of System-wise Evaluation". SIGDIAL(2020) [paper]
  • FED: "Unsupervised Evaluation of Interactive Dialog with DialoGPT". SIGDIAL(2020) [paper] [code] [data] ⭐⭐⭐
  • Spot-the-Bot: "Spot The Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems". EMNLP(2020) [paper] [code]
  • CMADE: "Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation". ACL(2020) [paper] [code]
  • Coherence: "Dialogue Coherence Assessment Without Explicit Dialogue Act Labels". ACL(2020) [paper] [code]
  • MAUDE: "Learning an Unreferenced Metric for Online Dialogue Evaluation". ACL(2020) [paper] [code]
  • GRADE: "GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems". ACL(2020) [paper] [code]
  • uBLEU: "uBLEU: Uncertainty-Aware Automatic Evaluation Method for Open-Domain Dialogue Systems". ACL(2020) [paper] [code]
  • USR: "USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation". ACL(2020) [paper] [code]
  • ACUTE-EVAL: "ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisons". NIPS ConvAI Workshop(2019) [paper] [code] ⭐⭐⭐
  • InteractiveEval: "Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems". NeurIPS(2019) [paper] [code] ⭐⭐⭐
  • ChatEval: "ChatEval: A Tool for Chatbot Evaluation". NAACL(2019) [paper] [project]
  • ADVMT: "One Ruler for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning". IJCAI(2018) [paper]

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Dialogue Misc.

  • Signed-dialogue: "Generating Signed Language Instructions in Large-Scale Dialogue Systems". NAACL(2024) [paper] [data]
  • Dialogue-KT: "Exploring Knowledge Tracing in Tutor-Student Dialogues". arXiv(2024) [paper] [code]
  • MathDial: "MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems". EMNLP-Findings(2023) [paper] [data]
  • EduChat: "EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education". arXiv(2023) [paper] [code]
  • ACT: "Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training". arXiv(2024) [paper]
  • ReviewMT: "Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions". arXiv(2024) [paper] [code]
  • WildChat: "WildChat: 1M ChatGPT Interaction Logs in the Wild". ICLR(2024) [paper] [data]
  • DialOp: "Decision-Oriented Dialogue for Human-AI Collaboration". arXiv(2023) [paper] [code] ⭐⭐⭐
  • DialogStudio: "DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI". arXiv(2023) [paper] [code]
  • MPC: "Multi-Party Chat: Conversational Agents in Group Settings with Humans and Models". arXiv(2023) [paper] [code]
  • SODA: "SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization". EMNLP(2023) [paper] [code] ⭐⭐⭐
  • speaker-adaptation: "Speaking the Language of Your Listener: Audience-Aware Adaptation via Plug-and-Play Theory of Mind". ACL-Findings(2023) [paper] [code]
  • SocialDial: "SocialDial: A Benchmark for Socially-Aware Dialogue Systems". SIGIR(2023) [paper] [data]
  • BotsTalk: "BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets". EMNLP(2022) [paper] [code]
  • Dialogic: "Dialogic: Controllable Dialogue Simulation with In-Context Learning". EMNLP-Findings(2022) [paper] [code]
  • ProsocialDialog: "ProsocialDialog: A Prosocial Backbone for Conversational Agents". EMNLP(2022) [paper] [code]
  • MIC: "The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems". ACL(2022) [paper] [code]
  • MoralDial: "MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Constructing Moral Discussions". arXiv(2022) [paper]
  • DECODE: "I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling". ACL(2021) [paper] [code]

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Natural Language Generation

Survey on NLG

  • CTG: "A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models". arXiv(2022) [paper]
  • RTG: "A Survey on Retrieval-Augmented Text Generation". arXiv(2022) [paper]
  • Hallucination: "Survey of Hallucination in Natural Language Generation". arXiv(2022) [paper]
  • Evaluation: "A Survey of Evaluation Metrics Used for NLG Systems". arXiv(2020) [paper]

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NLG Theories and Techniques

  • RED: "Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder". arXiv(2023) [paper] ⭐⭐⭐
  • LaMemo: "LaMemo: Language Modeling with Look-Ahead Memory". NAACL(2022) [paper] [code]
  • PTG: "Learning to Transfer Prompts for Text Generation". NAACL(2022) [paper] [code]
  • EISL: "Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation". NAACL(2022) [paper] [code]
  • CT-Loss: "A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration". arXiv(2022) [paper] [code]
  • SimCTG: "A Contrastive Framework for Neural Text Generation". NeurIPS(2022) [paper] [code] ⭐⭐⭐
  • CoNT: "CoNT: Contrastive Neural Text Generation". NeurIPS(2022) [paper] [code]
  • Two-level-CL: "Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation". ACL(2022) [paper]
  • CLAPS: "Contrastive Learning with Adversarial Perturbations for Conditional Text Generation". ICLR(2021) [paper] [code] ⭐⭐⭐⭐
  • RetGen: "RetGen: A Joint framework for Retrieval and Grounded Text Generation Modeling". AAAI(2022) [paper] [code]
  • RAG: "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks". NeurIPS(2020) [paper] [code] ⭐⭐⭐⭐
  • TextGAIL: "TextGAIL: Generative Adversarial Imitation Learning for Text Generation". AAAI(2021) [paper] [code]
  • Latent-GLAT: "latent-GLAT: Glancing at Latent Variables for Parallel Text Generation". ACL(2022) [paper] [code]
  • s2s-ft: "s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning". arXiv(2021) [paper] [code]
  • EBM: "Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation?". EMNLP(2021) [paper]
  • DiscoDVT: "DiscoDVT: Generating Long Text with Discourse-Aware Discrete Variational Transformer". EMNLP(2021) [paper] [code]
  • DATG: "Data Augmentation for Text Generation Without Any Augmented Data". ACL(2021) [paper]
  • JointGT: "JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs". ACL-Findings(2021) [paper] [code]
  • Embedding-Transfer: "Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation". ACL(2021) [paper] [code]
  • FastSeq: "EL-Attention: Memory Efficient Lossless Attention for Generation". ICML(2021) [paper] [code] ⭐⭐⭐
  • BERTSeq2Seq: "Leveraging Pre-trained Checkpoints for Sequence Generation Tasks". TACL(2020) [paper] [code-tf] [code-py] ⭐⭐⭐
  • ERNIE-GEN: "ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation". IJCAI(2020) [paper] [code] ⭐⭐⭐
  • DITTO: "Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation". NeurIPS(2022) [paper] [code]
  • Repetition-Problem: "A Theoretical Analysis of the Repetition Problem in Text Generation". AAAI(2021) [paper] [code]
  • ENCONTER: "ENCONTER: Entity Constrained Progressive Sequence Generation via Insertion-based Transformer". EACL(2021) [paper] [code]
  • POINTER: "POINTER: Constrained Progressive Text Generation via Insertion-based Generative Pre-training". EMNLP(2020) [paper] [code]
  • Cascaded Generation: "Cascaded Text Generation with Markov Transformers". NeurIPS(2020) [paper] [code]
  • SFOT: "Improving Text Generation with Student-Forcing Optimal Transport". EMNLP(2020) [paper]
  • OT-Seq2Seq: "Improving Sequence-to-Sequence Learning via Optimal Transport". ICLR(2019) [paper] [code]

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Diffusion Models for NLG

  • RenderDiffusion: "RenderDiffusion: Text Generation as Image Generation". arXiv(2023) [paper]
  • Masked-Diffusion-LM: "A Cheaper and Better Diffusion Language Model with Soft-Masked Noise". arXiv(2023) [paper] [code]
  • discrete-diffusion: "A Reparameterized Discrete Diffusion Model for Text Generation". arXiv(2023) [paper] [code]
  • Difformer: "Difformer: Empowering Diffusion Models on the Embedding Space for Text Generation". arXiv(2023) [paper] ⭐⭐⭐
  • GENIE: "Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise". arXiv(2022) [paper] [code]
  • SED: "Self-conditioned Embedding Diffusion for Text Generation". arXiv(2022) [paper]
  • SSD-LM: "SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control". arXiv(2022) [paper] [code]
  • LD4LG: "Latent Diffusion for Language Generation". arXiv(2022) [paper] [code]
  • DiffusionBERT: "DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models". arXiv(2022) [paper] [code]
  • DiffusER: "DiffusER: Discrete Diffusion via Edit-based Reconstruction". arXiv(2022) [paper] [code]
  • SeqDiffuSeq: "SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers". arXiv(2022) [paper] [code]
  • DiffuSeq: "DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models". ICLR(2023) [paper] [code]
  • Diffusion-LM: "Diffusion-LM Improves Controllable Text Generation". NeurIPS(2022) [paper] [code] ⭐⭐⭐
  • D3PM: "Structured Denoising Diffusion Models in Discrete State-Spaces". NeurIPS(2021) [paper] [code]

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Controllable Generation

  • ConGenBench: "Controllable Text Generation in the Instruction-Tuning Era". arXiv(2024) [paper] [code]
  • GeLaTo: "Tractable Control for Autoregressive Language Generation". arXiv(2023) [paper]
  • Cognac: "Controllable Text Generation with Language Constraints". arXiv(2022) [paper] [code]
  • CriticControl: "Critic-Guided Decoding for Controlled Text Generation". arXiv(2022) [paper]
  • LatentOps: "Composable Text Controls in Latent Space with ODEs". arXiv(2022) [paper] [code]
  • FAST: "FAST: Improving Controllability for Text Generation with Feedback Aware Self-Training". arXiv(2022) [paper]
  • DisCup: "DisCup: Discriminator Cooperative Unlikelihood Prompt-tuning for Controllable Text Generation". EMNLP(2022) [paper] [code]
  • MultiControl: "A Distributional Lens for Multi-Aspect Controllable Text Generation". EMNLP(2022) [paper] [code]
  • NADO: "Controllable Text Generation with Neurally-Decomposed Oracle". NeurIPS(2022) [paper] [code]
  • Mix-Match: "Mix and Match: Learning-free Controllable Text Generation using Energy Language Models". ACL(2022) [paper] [code]
  • ControlPrefix: "Controllable Natural Language Generation with Contrastive Prefixes". ACL-Findings(2022) [paper]
  • MUCOCO: "Controlled Text Generation as Continuous Optimization with Multiple Constraints". NeurIPS(2021) [paper] [code]
  • DExperts: "DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts". ACL(2021) [paper] [code]
  • FUDGE: "FUDGE: Controlled Text Generation With Future Discriminators". NAACL(2021) [paper] [code]
  • GeDi: "GeDi: Generative Discriminator Guided Sequence Generation". EMNLP-Findings(2021) [paper] [code]
  • GDC: "A Distributional Approach to Controlled Text Generation". ICLR(2021) [paper] [code] ⭐⭐⭐
  • CoCon: "CoCon: A Self-Supervised Approach for Controlled Text Generation". ICLR(2021) [paper] [code]
  • PPLM: "Plug and Play Language Models: A Simple Approach to Controlled Text Generation". ICLR(2020) [paper] [code] ⭐⭐⭐
  • CTRL: "CTRL: A Conditional Transformer Language Model for Controllable Generation". arXiv(2019) [paper] [code]

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Text Planning

  • CoScript: "Distilling Script Knowledge from Large Language Models for Constrained Language Planning". ACL(2023) [paper] [code]
  • RSTGen: "RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators". NAACL(2022) [paper]
  • Time Control: "Language Modeling via Stochastic Processes". ICLR(2022) [paper] [code] ⭐⭐⭐⭐⭐
  • PLANET: "PLANET: Dynamic Content Planning in Autoregressive Transformers for Long-form Text Generation". ACL(2022) [paper]
  • EventPlan: "Event Transition Planning for Open-ended Text Generation". ACL-Findings(2022) [paper] [code]
  • CETP: "Knowledge-based Review Generation by Coherence Enhanced Text Planning". SIGIR(2021) [paper] ⭐⭐⭐
  • PlanGen: "Plan-then-Generate: Controlled Data-to-Text Generation via Planning". EMNLP-Findings(2021) [paper] [code]
  • DYPLOC: "DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation". ACL(2021) [paper] [code]
  • Tree-PLAN: "Infobox-to-text Generation with Tree-like Planning based Attention Network". IJCAI(2020) [paper]
  • ProphetNet: "ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training". EMNLP-Findings(2020) [paper] [code] ⭐⭐⭐
  • PAIR: "PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation". EMNLP(2020) [paper] [code]
  • SentPlan: "Sentence-Level Content Planning and Style Specification for Neural Text Generation". EMNLP(2019) [paper] [code]
  • PHVM: "Long and Diverse Text Generation with Planning-based Hierarchical Variational Model". EMNLP(2019) [paper] [code]
  • TwinNet: "Twin Networks: Matching the Future for Sequence Generation". ICLR(2018) [paper] [code]
  • PAG: "Plan, Attend, Generate: Planning for Sequence-to-Sequence Models". NIPS(2017) [paper]

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Decoding Algorithms

  • Speculative Decoding: "Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation". EMNLP-Findings(2023) [paper] [code] ⭐⭐⭐
  • Medusa: "Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads". Github(2023) [Blog] [code]
  • Lookahead Decoding: "Breaking the Sequential Dependency of LLM Inference Using Lookahead Decoding". LMSYS Org(2023) [Blog] [code] ⭐⭐⭐
  • Speculative Sampling: "Accelerating Large Language Model Decoding with Speculative Sampling". arXiv(2023) [paper]
  • Speculative Decoding: "Fast Inference from Transformers via Speculative Decoding". ICML(2023) [paper] [code]
  • Parallel Decoding: "Accelerating Transformer Inference for Translation via Parallel Decoding". ACL(2023) [paper] [code]
  • EAD: "The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation". arXiv(2023) [paper] [code]
  • Contrastive Search: "Contrastive Search Is What You Need For Neural Text Generation". TMLR(2023) [paper] [code] [blog] ⭐⭐⭐
  • Momentum Decoding: "Momentum Decoding: Open-ended Text Generation As Graph Exploration". arXiv(2022) [paper] [code]
  • Crowd Sampling: "Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding". arXiv(2022) [paper] [code]
  • RankGen: "RankGen: Improving Text Generation with Large Ranking Models". EMNLP(2022) [paper] [code]
  • Contrastive Decoding: "Contrastive Decoding: Open-ended Text Generation as Optimization". arXiv(2022) [paper] [code]
  • COLD: "COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics". NeurIPS(2022) [paper] [code] ⭐⭐⭐
  • Lattice: "Massive-scale Decoding for Text Generation using Lattices". NAACL(2022) [paper] [code]
  • KID: "Knowledge Infused Decoding". ICLR(2022) [paper] [code]
  • NeuroLogic A*esque: "NeuroLogic A *esque Decoding: Constrained Text Generation with Lookahead Heuristics". NAACL(2022) [paper] [code]
  • NeuroLogic: "NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints". NAACL(2021) [paper] [code]
  • DeLorean: "Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning". EMNLP(2020) [paper] [code]
  • Top-p (Nucleus) Sampling: "The Curious Case of Neural Text Degeneration". ICLR(2020) [paper] [code] ⭐⭐⭐
  • BP Decoding: "Blockwise Parallel Decoding for Deep Autoregressive Models". NIPS(2018) [paper]
  • Disjunctive Constraints: "Guided Generation of Cause and Effect". IJCAI(2020) [paper] [code-huggingface]
  • CGMH: "CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling". AAAI(2019) [paper] [code]
  • DBS: "Directed Beam Search: Plug-and-Play Lexically Constrained Language Generation". arXiv(2020) [paper] [code]
  • DBA: "Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation". NAACL(2018) [paper] [code-official] [code-fairseq]
  • GBS: "Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search". ACL(2017) [paper] [code]

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NLG Evaluation

  • Survey: "Leveraging Large Language Models for NLG Evaluation: A Survey". arXiv(2024) [paper]
  • BBScore: "BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence". AAAI(2024) [paper]
  • GPTEval: "GPTEval: NLG Evaluation using GPT-4 with Better Human Alignment". arXiv(2023) [paper]
  • GPTScore: "GPTScore: Evaluate as You Desire". arXiv(2023) [paper] [code]
  • RoMe: "RoMe: A Robust Metric for Evaluating Natural Language Generation". ACL(2022) [paper] [code]
  • EAD: "Rethinking and Refining the Distinct Metric". ACL(2022) [paper] [code]
  • MID: "Mutual Information Divergence: A Unified Metric for Multimodal Generative Models". NeurIPS(2022) [paper]
  • DiscoScore: "DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence". arXiv(2022) [paper] [code]
  • CTC-Score: "Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation". EMNLP(2021) [paper] [code]
  • BLEURT: "BLEURT: Learning Robust Metrics for Text Generation". ACL(2020) [paper] [code]

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