mlsanityData to 14 Oct 2026

AMR Parsing using Stack-LSTMs

arXiv 1707.07755 ↗First posted 24 Jul 2017cs.CLcited by 15

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Abstract (arXiv)

We present a transition-based AMR parser that directly generates AMR parses from plain text. We use Stack-LSTMs to represent our parser state and make decisions greedily. In our experiments, we show that our parser achieves very competitive scores on English using only AMR training data. Adding additional information, such as POS tags and dependency trees, improves the results further.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jul 2017.

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Citing papers per year: 2021: 4; 2022: 6; 2023: 3; 2024: 1; 2025: 1.

15 papers.

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  1. 2022Graph Pre-training for AMR Parsing and Generationcited by 55
  2. 2021AMR Parsing with Action-Pointer Transformercited by 25
  3. 2021Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsingcited by 25
  4. 2022Inducing and Using Alignments for Transition-based AMR Parsingcited by 12
  5. 2023ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translationcited by 11
  6. 2021Bootstrapping Multilingual AMR with Contextual Word Alignmentscited by 8
  7. 2023Incorporating Graph Information in Transformer-based AMR Parsingcited by 7
  8. 2021Levi Graph AMR Parser using Heterogeneous Attentioncited by 2
  9. 2022Cross-domain Generalization for AMR Parsingcited by 2
  10. 2022Dependency Parsing with Backtracking using Deep Reinforcement Learningcited by 1
  11. 2023AMR Parsing with Causal Hierarchical Attention and Pointerscited by 1
  12. 2024Adapting Abstract Meaning Representation Parsing to the Clinical Narrative -- the SPRING THYME parsercited by 1
3 more
  1. 2022Shift-Reduce Task-Oriented Semantic Parsing with Stack-Transformerscited by 0
  2. 2022Strictly Breadth-First AMR Parsingcited by 0
  3. 2025Evaluation of Finetuned LLMs in AMR Parsingcited by 0