/AMR-Literature

Resources to conference/journal publications related to AMR (Abstract Meaning Representation).

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AMR-Literature

This repo contains relevant resources related to AMR (Abstract Meaning Representation).

AMR Parsing

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Conference & Journal Paper

  • A differentiable relaxation of graph segmentation and alignment for amr parsing. [Paper] [Bib] EMNLP2021
  • Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing. [Paper] [Code] [Bib] EMNLP2021
  • Stacked AMR Parsing with Silver Data. [Paper] [Code] [Bib] Findings ACL2021
  • Ensembling Graph Predictions for AMR Parsing. [Paper] [Code] [Bib] NeurIPS2021
  • AMR parsing with action-pointer transformer. [Paper] [Code] [Bib] NAACL2021
  • One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline. [Paper] [Code] [Bib] **AAAI2021
  • Improving AMR Parsing with Sequence-to-Sequence Pre-training. [Paper] [Code] [Bib] EMNLP2020
  • Fast semantic parsing with well-typedness guarantees. [Paper] [Code] [Bib] EMNLP2020
  • Pushing the Limits of AMR Parsing with Self-Learning. [Paper] [Code] [Bib] Findings EMNLP2020
  • Transition-based Parsing with Stack-Transformers. [Paper] [Code] [Bib] Findings EMNLP2020
  • AMR Parsing via Graph-Sequence Iterative Inference. [Paper] [Code] [Bib] ACL2020
  • Core Semantic First: A Top-down Approach for AMR Parsing. [Paper] [Code] [Bib] EMNLP2019
  • Broad-coverage semantic parsing as transduction. [Paper] [Code] [Bib] EMNLP2019
  • AMR parsing as sequence-to-graph transduction. [Paper] [Code] [Bib] ACL2019
  • Rewarding Smatch: Transition-based AMR parsing with reinforcement learning. [Paper] [Code] [Bib] ACL2019
  • Better transition-based AMR parsing with a refined search space. [Paper] [Code] [Bib] EMNLP2018
  • AMR parsing as graph prediction with latent alignment. [Paper] [Code] [Bib] ACL2018
  • AMR parsing using stack-LSTMs. [Paper] [Code] [Bib] EMNLP2017
  • Getting the most out of amr parsing. [Paper] [Code] [Bib] EMNLP2017
  • Robust incremental neural semantic graph parsing. [Paper] [Code] [Bib] ACL2017
  • Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. [Paper] [Code] [Bib] ACL2017
  • A constrained graph algebra for semantic parsing with AMRs. [Paper] [Code] [Bib] IWCS2017
  • Neural Shift-Reduce CCG Semantic Parsing. [Paper] [Code] [Bib] EMNLP2016
  • AMR Parsing with an Incremental Joint Model. [Paper] [Code] [Bib] EMNLP2016
  • Noise Reduction and Targeted Exploration in Imitation Learning for Abstract Meaning Representation Parsing. [Paper] [Code] [Bib] ACL2016
  • An incremental parser for abstract meaning representation. [Paper] [Code] [Bib] EACL2016
  • Generation from Abstract Meaning Representation using Tree Transducers. [Paper] [Code] [Bib] NAACL2016
  • Between a Rock and a Hard Place -- Uniform Parsing for Hyperedge Replacement DAG Grammars. [Paper] [Code] [Bib] LATA 2016
  • Broad-coverage CCG Semantic Parsing with AMR. [Paper] [Code] [Bib] EMNLP2015
  • Using Syntax-Based Machine Translation to Parse English into Abstract Meaning Representation. [Paper] [Code] [Bib] EMNLP2015
  • A Synchronous Hyperedge Replacement Grammar based approach for AMR parsing. [Paper] [Code] [Bib] CoNLL2015
  • Robust Subgraph Generation Improves Abstract Meaning Representation Parsing. [Paper] [Code] [Bib] ACL2015
  • Graph parsing with s-graph grammars. [Paper] [Code] [Bib] ACL2015
  • Boosting Transition-based AMR Parsing with Refined Actions and Auxiliary Analyzers. [Paper] [Code] [Bib] ACL2015
  • A transition-based algorithm for AMR parsing. [Paper] [Code] [Bib] NAACL2015
  • A Discriminative Graph-Based Parser for the Abstract Meaning Representation. [Paper] [Code] [Bib] ACL2014

Shared Task Paper

  • Oxford at SemEval-2017 Task 9: Neural AMR Parsing with Pointer-Augmented Attention. [Paper] [Code] [Bib] SemEval2017
  • SemEval-2017 Task 9: Abstract Meaning Representation Parsing and Generation. [Paper] [Code] [Bib] SemEval2017
  • RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generatio. [Paper] [Code] [Bib] SemEval2017
  • CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss. [Paper] [Code] [Bib] SemEval2016
  • UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound. [Paper] [Code] [Bib] SemEval2016
  • CAMR at SemEval-2016 Task 8: An Extended Transition-based AMR Parser. [Paper] [Code] [Bib] SemEval2016
  • CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks. [Paper] [Code] [Bib] SemEval2016
  • ICL-HD at SemEval-2016 Task 8: Meaning Representation Parsing - Augmenting AMR Parsing with a Preposition Semantic Role Labeling Neural Network. [Paper] [Code] [Bib] SemEval2016
  • CLIP@UMD at SemEval-2016 Task 8: Parser for Abstract Meaning Representation using Learning to Search. [Paper] [Code] [Bib] SemEval2016
  • UofR at SemEval-2016 Task 8: Learning Synchronous Hyperedge Replacement Grammar for AMR Parsing. [Paper] [Code] [Bib] SemEval2016
  • M2L at SemEval-2016 Task 8: AMR Parsing with Neural Networks. [Paper] [Code] [Bib] SemEval2016
  • RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy. [Paper] [Code] [Bib] SemEval2016

Multilingual/Cross-Lingual AMR Parsing

  • Multilingual AMR Parsing with Noisy Knowledge Distillation. Findings EMNLP2021
  • Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing. Findings ACL2021
  • Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing. IWPT2021
  • An AMR parser for English, French, German, Spanish and Japanese and a new AMR-annotated corpus. Demo NAACL2015

AMR-to-Text Generation

Generation

  • Structural Adapters in Pretrained Language Models for AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2021
  • Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2021
  • Avoiding Overlap in Data Augmentation for AMR-to-Text Generation. [Paper] [Code] [Bib] ACL2021
  • Stage-wise Fine-tuning for Graph-to-Text Generation. [Paper] [Code] [Bib] ACL2021
  • Generating Landmark Navigation Instructions from Maps as a Graph-to-Text Problem. [Paper] [Code] [Bib] ACL2021
  • XLPT-AMR: Cross-Lingual Pre-Training via Multi-Task Learning for Zero-Shot AMR Parsing and Text Generation.
    [Paper] [Code] [Bib] ACL2021
  • DART: Open-Domain Structured Data Record to Text Generation. [Paper] [Code] [Bib] NAACL2021
  • Multilingual AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2020
  • Online Back-Parsing for AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2020
  • Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2020
  • Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks. [Paper] [Code] [Bib] ACL2020
  • GPT-too: A language-model-first approach for AMR-to-text generation. [Paper] [Code] [Bib] ACL2020
  • AMR-To-Text Generation with Graph Transformer. [Paper] [Code] [Bib] TACL2020
  • Graph Transformer for Graph-to-Sequence Learning. [Paper] [Code] [Bib] AAAI2020
  • Heterogeneous Graph Transformer for Graph-to-Sequence Learning. [Paper] [Code] [Bib] ACL2020
  • structural information preserving for graph-to-text generation. [Paper] [Code] [Bib] ACL2020
  • Generalized Shortest-Paths Encoders for AMR-to-Text Generation. [Paper] [Code] [Bib] COLING2020
  • Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR. [Paper] [Code] [Bib] EACL2020
  • Better AMR-To-Text Generation with Graph Structure Reconstruction. [Paper] [Code] [Bib] IJCAI2020
  • Modeling Graph Structure in Transformer for Better AMR-to-Text Generation. [Paper] [Code] [Bib] EMNLP2019
  • Enhancing AMR-to-Text Generation with Dual Graph Representations. [Paper] [Code] [Bib] EMNLP2019
  • Structural Neural Encoders for AMR-to-text Generation. [Paper] [Code] [Bib] NAACL2019
  • Factorising AMR generation through syntax. [Paper] [Code] [Bib] NAACL2019
  • Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning.
    [Paper] [Code] [Bib] TACL2019
  • Deep Graph Convolutional Encoders for Structured Data to Text Generation. [Paper] [Code] [Bib] INLG2018
  • A Graph-to-Sequence Model for AMR-to-Text Generation. [Paper] [Code] [Bib] ACL2018
  • Graph-to-Sequence Learning using Gated Graph Neural Networks. [Paper] [Code] [Bib] ACL2018
  • Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. [Paper] [Code] [Bib] ACL2017
  • AMR-to-text Generation with Synchronous Node Replacement Grammar. [Paper] [Code] [Bib] ACL2017
  • AMR-to-text generation as a Traveling Salesman Problem. [Paper] [Code] [Bib] EMNLP2016
  • Generation from Abstract Meaning Representation using Tree Transducers. [Paper] [Code] [Bib] NAACL2016
  • Generating English from Abstract Meaning Representations. [Paper] [Code] [Bib] INLG2016

Applications using AMR

  • A Semantics-aware Transformer Model of Relation Linking for Knowledge Base Question Answering. ACL2021
  • Leveraging Abstract Meaning Representation for knowledge base question answering. Findings ACL2021