Deep Cognition and Language Research (DeCLaRe) Lab

awesome-emotion-recognition-in-conversations

A comprehensive reading list for Emotion Recognition in Conversations

awesome-sentiment-analysis

Reading list for Awesome Sentiment Analysis papers

conv-emotion

This repo contains implementation of different architectures for emotion recognition in conversations.

flan-alpaca

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

instruct-eval

This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.

MELD

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

multimodal-deep-learning

This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.

nora

NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks

tango

A family of diffusion models for text-to-audio generation.

TangoFlux

TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching

declare-lab/multimodal-deep-learning

This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.

declare-lab/awesome-sentiment-analysis

Reading list for Awesome Sentiment Analysis papers

declare-lab/flan-alpaca

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

declare-lab/awesome-emotion-recognition-in-conversations

A comprehensive reading list for Emotion Recognition in Conversations

declare-lab/MISA

MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis

declare-lab/Multimodal-Infomax

This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis, accepted at EMNLP 2021.

declare-lab/RelationPrompt

This repository implements our ACL Findings 2022 research paper RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction. The goal of Zero-Shot Relation Triplet Extraction (ZeroRTE) is to extract relation triplets of the format (head entity, tail entity, relation), despite not having annotated data for the test relation labels.

declare-lab/dialogue-understanding

This repository contains PyTorch implementation for the baseline models from the paper Utterance-level Dialogue Understanding: An Empirical Study

declare-lab/contextual-utterance-level-multimodal-sentiment-analysis

Context-Dependent Sentiment Analysis in User-Generated Videos

declare-lab/flacuna

Flacuna was developed by fine-tuning Vicuna on Flan-mini, a comprehensive instruction collection encompassing various tasks. Vicuna is already an excellent writing assistant, and the intention behind Flacuna was to enhance Vicuna's problem-solving capabilities. To achieve this, we curated a dedicated instruction dataset called Flan-mini.

declare-lab/CASCADE

This repo contains code to detect sarcasm from text in discussion forum using deep learning

declare-lab/BBFN

This repository contains the implementation of the paper -- Bi-Bimodal Modality Fusion for Correlation-Controlled Multimodal Sentiment Analysis

declare-lab/CICERO

The purpose of this repository is to introduce new dialogue-level commonsense inference datasets and tasks. We chose dialogues as the data source because dialogues are known to be complex and rich in commonsense.

declare-lab/kingdom

Domain Adaptation using External Knowledge for Sentiment Analysis

declare-lab/hfusion

Multimodal sentiment analysis using hierarchical fusion with context modeling

declare-lab/MIME

This repository contains PyTorch implementations of the models from the paper An Empirical Study MIME: MIMicking Emotions for Empathetic Response Generation.

declare-lab/speech-adapters

Codes and datasets for our ICASSP2023 paper, Evaluating parameter-efficient transfer learning approaches on SURE benchmark for speech understanding

declare-lab/sentence-ordering

This repository contains the PyTorch implementation of the paper STaCK: Sentence Ordering with Temporal Commonsense Knowledge appearing at EMNLP 2021.

declare-lab/identifiable-transformers

declare-lab/ASTE-RL

This repository contains the source codes for the paper: "Aspect Sentiment Triplet Extraction using Reinforcement Learning" published at CIKM 2021.

declare-lab/M2H2-dataset

This repository contains the dataset and baselines explained in the paper: M2H2: A Multimodal Multiparty Hindi Dataset For HumorRecognition in Conversations

declare-lab/WikiDes

A Wikipedia-based summarization dataset

declare-lab/SAT

Code for the EMNLP 2022 Findings short paper "SAT: Improving Semi-Supervised Text Classification with Simple Instance-Adaptive Self-Training"

declare-lab/domadapter

Code for EACL'23 paper "Udapter: Efficient Domain Adaptation Using Adapters"

declare-lab/LG-VQA

declare-lab/SANCL

[COLING 2022] This repository contains the code of the paper SANCL: Multimodal Review Helpfulness Prediction with Selective Attention and Natural Contrastive Learning.

declare-lab/segue

Codes and Checkpoints of the Interspeech paper "Sentence Embedder Guided Utterance Encoder (SEGUE) for Spoken Language Understanding"

declare-lab/DPR

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

declare-lab/Video2Music

Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model

declare-lab/mustango

Mustango: Toward Controllable Text-to-Music Generation