# Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning

arXiv: https://arxiv.org/abs/1905.13370 · HTML: https://mlsanity.com/paper/1905.13370/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 May 2019.

## Built on by (most cited first, 25 of 25)

- [Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://mlsanity.com/paper/2111.01243/) (2021)
- [Maximum Bayes Smatch Ensemble Distillation for AMR Parsing](https://mlsanity.com/paper/2112.07790/) (2021)
- [AMR Parsing with Action-Pointer Transformer](https://mlsanity.com/paper/2104.14674/) (2021)
- [Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing](https://mlsanity.com/paper/2110.15534/) (2021)
- [Weisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity](https://mlsanity.com/paper/2108.11949/) (2021)
- [Inducing and Using Alignments for Transition-based AMR Parsing](https://mlsanity.com/paper/2205.01464/) (2022)
- [ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation](https://mlsanity.com/paper/2305.16585/) (2023)
- [Hierarchical Curriculum Learning for AMR Parsing](https://mlsanity.com/paper/2110.07855/) (2021)
- [Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignments](https://mlsanity.com/paper/2106.06002/) (2021)
- [Bootstrapping Multilingual AMR with Contextual Word Alignments](https://mlsanity.com/paper/2102.02189/) (2021)
- [ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs](https://mlsanity.com/paper/2204.08875/) (2022)
- [Levi Graph AMR Parser using Heterogeneous Attention](https://mlsanity.com/paper/2107.04152/) (2021)
- [Scene Graph Modification as Incremental Structure Expanding](https://mlsanity.com/paper/2209.09093/) (2022)
- [Cross-domain Generalization for AMR Parsing](https://mlsanity.com/paper/2210.12445/) (2022)
- [Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing](https://mlsanity.com/paper/2106.04814/) (2021)
- [Dependency Parsing with Backtracking using Deep Reinforcement Learning](https://mlsanity.com/paper/2206.13914/) (2022)
- [AMR Parsing with Causal Hierarchical Attention and Pointers](https://mlsanity.com/paper/2310.11964/) (2023)
- [SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph Distance](https://mlsanity.com/paper/2203.13226/) (2022)
- [Transition-based Abstract Meaning Representation Parsing with Contextual Embeddings](https://mlsanity.com/paper/2206.06229/) (2022)
- [Strictly Breadth-First AMR Parsing](https://mlsanity.com/paper/2211.03922/) (2022)
- [Slide, Constrain, Parse, Repeat: Synchronous SlidingWindows for Document AMR Parsing](https://mlsanity.com/paper/2305.17273/) (2023)
- [Guiding AMR Parsing with Reverse Graph Linearization](https://mlsanity.com/paper/2310.08860/) (2023)
- [FLAG: Financial Long Document Classification via AMR-based GNN](https://mlsanity.com/paper/2410.02024/) (2024)
- [Evaluation of Finetuned LLMs in AMR Parsing](https://mlsanity.com/paper/2508.05028/) (2025)
- [Object Aligner: A Configurable JSON Schema Similarity Score for Graphs, Applied to LLM Prompt Optimization](https://mlsanity.com/paper/2607.01972/) (2026)

## Abstract (arXiv)

Our work involves enriching the Stack-LSTM transition-based AMR parser (Ballesteros and Al-Onaizan, 2017) by augmenting training with Policy Learning and rewarding the Smatch score of sampled graphs. In addition, we also combined several AMR-to-text alignments with an attention mechanism and we supplemented the parser with pre-processed concept identification, named entities and contextualized embeddings. We achieve a highly competitive performance that is comparable to the best published results. We show an in-depth study ablating each of the new components of the parser