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# Who cites «Neural AMR: Sequence-to-Sequence Models for Parsing and Generation»

173 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/konstas-2017-neural-amr-sequence-sequence-models/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/konstas-2017-neural-amr-sequence-sequence-models-2/)

1. [Emphasising Structured Information: Integrating Abstract Meaning Representation into LLMs for Enhanced Open-Domain Dialogue Evaluation](https://aclanthology.org/2025.findings-emnlp.1096/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
2. [Enhancing AMR Parsing with Group Relative Policy Optimization](https://aclanthology.org/2025.xllm-1.11/) *— 2025 · Proceedings of the 1st Joint Workshop on Large Language Models and Structure Modeling (XLLM 2025)*
3. [Reassessing Graph Linearization for Sequence-to-sequence AMR Parsing: On the Advantages and Limitations of Triple-Based Encoding](https://arxiv.org/abs/2505.08504) *— 2025 · arXiv:2505.08504*
4. [SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation](https://arxiv.org/abs/2507.13381) *— 2025 · arXiv:2507.13381*
5. [Semantic Bridge: Universal Multi-Hop Question Generation via AMR-Driven Graph Synthesis](https://arxiv.org/abs/2508.10013) *— 2025 · arXiv:2508.10013*
6. [Survey of Abstract Meaning Representation: Then, Now, Future](https://md.mova.elamur.ai/free/en/docs/papers/mansouri-2025-survey-abstract-meaning-representation-then/) *— our card · 2025 · arXiv:2505.03229*
7. [ViAMR: Fine-tuning LLMs for Abstract Meaning Representation in Vietnamese](https://aclanthology.org/2025.vlsp-1.31/) *— 2025 · Proceedings of the 11th International Workshop on Vietnamese Language and Speech Processing*
8. [Adapting Abstract Meaning Representation Parsing to the Clinical Narrative – the SPRING THYME parser](https://aclanthology.org/2024.clinicalnlp-1.23/) *— 2024 · Proceedings of the 6th Clinical Natural Language Processing Workshop*
9. [Leveraging AMR Graph Structure for Better Sequence-to-Sequence AMR Parsing](https://aclanthology.org/2024.lrec-main.903/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
10. [Linearization Order Matters for AMR-to-Text Generation Input](https://aclanthology.org/2024.umrpw-1.1/) *— 2024 · Proceedings of the 2024 UMR Parsing Workshop*
11. [Linguistic Guidance for Sequence-to-Sequence AMR Parsing](https://aclanthology.org/2024.ccl-1.94/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)*
12. [Prompting for Numerical Sequences: A Case Study on Market Comment Generation](https://aclanthology.org/2024.lrec-main.1155/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
13. [Semantic Graphs for Syntactic Simplification: A Revisit from the Age of LLM](https://aclanthology.org/2024.textgraphs-1.8/) *— 2024 · Proceedings of TextGraphs-17: Graph-based Methods for Natural Language Processing*
14. [基于样本设计工程和大模型微调的中文意合图语义解析\ensuremath*](https://aclanthology.org/2024.ccl-3.8/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)*
15. [面向中文抽象语义表示解析的大模型评估与增强](https://aclanthology.org/2024.ccl-3.15/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)*
16. [AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Model](https://aclanthology.org/2023.acl-long.615/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
17. [AMR Parsing with Causal Hierarchical Attention and Pointers](https://aclanthology.org/2023.emnlp-main.553/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
18. [CCL23-Eval 任务2系统报告:WestlakeNLP,基于生成式大语言模型的中文抽象语义表示解析(System Report for CCL23-Eval Task 2: WestlakeNLP, Investigating Generative Large Language Models for Chinese AMR Parsing)](https://aclanthology.org/2023.ccl-3.7/) *— 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)*
19. [Evaluating Generative Models for Graph-to-Text Generation](https://aclanthology.org/2023.ranlp-1.133/) *— 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing*
20. [Improving Medical Dialogue Generation with Abstract Meaning Representations](https://arxiv.org/abs/2309.10608) *— 2023 · arXiv:2309.10608*
21. [Investigating the Effect of Relative Positional Embeddings on AMR-to-Text Generation with Structural Adapters](https://aclanthology.org/2023.eacl-main.51/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
22. [ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation](https://md.mova.elamur.ai/free/en/docs/papers/huang-2023-paraamr-large-scale-syntactically-diverse/) *— our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Reinforced Sequence Training based Subjective Bias Correction](https://aclanthology.org/2023.eacl-main.189/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
24. [A Dynamic, Interpreted CheckList for Meaning-oriented NLG Metric Evaluation – through the Lens of Semantic Similarity Rating](https://aclanthology.org/2022.starsem-1.14/) *— 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics*
25. [AMR Alignment for Morphologically-rich and Pro-drop Languages](https://aclanthology.org/2022.acl-srw.13/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop*
26. [Align-smatch: A Novel Evaluation Method for Chinese Abstract Meaning Representation Parsing based on Alignment of Concept and Relation](https://aclanthology.org/2022.lrec-1.638/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
27. [BiBL: AMR Parsing and Generation with Bidirectional Bayesian Learning](https://aclanthology.org/2022.coling-1.485/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
28. [Can AMR Assist Legal and Logical Reasoning?](https://aclanthology.org/2022.findings-emnlp.112/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
29. [Graph Pre-training for AMR Parsing and Generation](https://aclanthology.org/2022.acl-long.415/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Improving Compositional Generalization with Self-Training for Data-to-Text Generation](https://aclanthology.org/2022.acl-long.289/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
31. [Maximum Bayes Smatch Ensemble Distillation for AMR Parsing](https://aclanthology.org/2022.naacl-main.393/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
32. [Meaning Representations for Natural Languages: Design, Models and Applications](https://aclanthology.org/2022.emnlp-tutorials.1/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts*
33. [Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification](https://aclanthology.org/2022.emnlp-main.314/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
34. [On The Ingredients of an Effective Zero-shot Semantic Parser](https://aclanthology.org/2022.acl-long.103/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
35. [Paraphrase Identification with Deep Learning: A Review of Datasets and Methods](https://arxiv.org/abs/2212.06933) *— 2022 · arXiv:2212.06933*
36. [Scene Graph Parsing via Abstract Meaning Representation in Pre-trained Language Models](https://aclanthology.org/2022.dlg4nlp-1.4/) *— 2022 · Proceedings of the 2nd Workshop on Deep Learning on Graphs for Natural Language Processing (DLG4NLP 2022)*
37. [Semantic-based Pre-training for Dialogue Understanding](https://aclanthology.org/2022.coling-1.49/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
38. [Sequence-to-sequence AMR Parsing with Ancestor Information](https://aclanthology.org/2022.acl-short.63/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
39. [Strictly Breadth-First AMR Parsing](https://arxiv.org/abs/2211.03922) *— 2022 · arXiv:2211.03922*
40. [Text-to-Text Extraction and Verbalization of Biomedical Event Graphs](https://aclanthology.org/2022.coling-1.238/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
41. [Towards Collaborative Neural-Symbolic Graph Semantic Parsing via Uncertainty](https://aclanthology.org/2022.findings-acl.328/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
42. [Transition-based Abstract Meaning Representation Parsing with Contextual Embeddings](https://arxiv.org/abs/2206.06229) *— 2022 · arXiv:2206.06229*
43. [Using Structured Content Plans for Fine-grained Syntactic Control in Pretrained Language Model Generation](https://aclanthology.org/2022.coling-1.514/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
44. [A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing](https://aclanthology.org/2021.emnlp-main.714/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
45. [An Error Analysis Framework for Shallow Surface Realization](https://md.mova.elamur.ai/free/en/docs/papers/shimorina-2021-error-analysis-framework-shallow-surface/) *— our card · 2021*
46. [AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models](https://aclanthology.org/2021.nlp4convai-1.19/) *— 2021 · Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI*
47. [Avoiding Overlap in Data Augmentation for AMR-to-Text Generation](https://aclanthology.org/2021.acl-short.132/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
48. [Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic Parsing](https://aclanthology.org/2021.cl-1.3/) *— 2021 · Computational Linguistics*
49. [Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing](https://aclanthology.org/2021.starsem-1.20/) *— 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics*
50. [Evaluating Text Generation from Discourse Representation Structures](https://md.mova.elamur.ai/free/en/docs/papers/wang-2021-evaluating-text-generation-discourse-representation/) *— our card · 2021 · Proceedings of the First Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
51. [Input Representations for Parsing Discourse Representation Structures: Comparing English with Chinese](https://aclanthology.org/2021.acl-short.97/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
52. [Investigating Pretrained Language Models for Graph-to-Text Generation](https://aclanthology.org/2021.nlp4convai-1.20/) *— 2021 · Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI*
53. [Latent Tree Decomposition Parsers for AMR-to-Text Generation](https://arxiv.org/abs/2108.12304) *— 2021 · arXiv:2108.12304*
54. [Levi Graph AMR Parser using Heterogeneous Attention](https://aclanthology.org/2021.iwpt-1.5/) *— 2021 · Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021)*
55. [Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing](https://aclanthology.org/2021.findings-acl.134/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
56. [Multilingual AMR Parsing with Noisy Knowledge Distillation](https://aclanthology.org/2021.findings-emnlp.237/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
57. [One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets](https://aclanthology.org/2021.starsem-1.16/) *— 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics*
58. [Promoting Graph Awareness in Linearized Graph-to-Text Generation](https://aclanthology.org/2021.findings-acl.82/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
59. [Revisiting Pivot-Based Paraphrase Generation: Language Is Not the Only Optional Pivot](https://aclanthology.org/2021.emnlp-main.350/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
60. [SGL: Speaking the Graph Languages of Semantic Parsing via Multilingual Translation](https://aclanthology.org/2021.naacl-main.30/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
61. [Semantic Representation for Dialogue Modeling](https://aclanthology.org/2021.acl-long.342/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
62. [Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation](https://aclanthology.org/2021.emnlp-main.57/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
63. [Stacked AMR Parsing with Silver Data](https://aclanthology.org/2021.findings-emnlp.406/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
64. [Structural Adapters in Pretrained Language Models for AMR-to-Text Generation](https://aclanthology.org/2021.emnlp-main.351/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
65. [Text Generation from Discourse Representation Structures](https://md.mova.elamur.ai/free/en/docs/papers/liu-2021-text-generation-discourse-representation-structures/) *— our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
66. [Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR](https://md.mova.elamur.ai/free/en/docs/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/) *— our card · 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
67. [Tree Decomposition Attention for AMR-to-Text Generation](https://arxiv.org/abs/2108.12300) *— 2021 · arXiv:2108.12300*
68. [A Human Evaluation of AMR-to-English Generation Systems](https://md.mova.elamur.ai/free/en/docs/papers/manning-2020-human-evaluation-amr-english-generation/) *— our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
69. [A Unifying Theory of Transition-based and Sequence Labeling Parsing](https://aclanthology.org/2020.coling-main.336/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
70. [ADAPT at SR''20: How Preprocessing and Data Augmentation Help to Improve Surface Realization](https://aclanthology.org/2020.msr-1.3/) *— 2020 · Proceedings of the Third Workshop on Multilingual Surface Realisation*
71. [AMR Parsing via Graph-Sequence Iterative Inference](https://aclanthology.org/2020.acl-main.119/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
72. [AMR Parsing with Latent Structural Information](https://aclanthology.org/2020.acl-main.397/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
73. [AMR Quality Rating with a Lightweight CNN](https://aclanthology.org/2020.aacl-main.27/) *— 2020 · Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing*
74. [AMR Similarity Metrics from Principles](https://aclanthology.org/2020.tacl-1.34/) *— 2020*
75. [AMR-To-Text Generation with Graph Transformer](https://aclanthology.org/2020.tacl-1.2/) *— 2020 · Transactions of the Association for Computational Linguistics*
76. [Autoregressive Entity Retrieval](https://arxiv.org/abs/2010.00904) *— 2020 · arXiv:2010.00904*
77. [Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems](https://aclanthology.org/2020.coling-industry.2/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics: Industry Track*
78. [ENT-DESC: Entity Description Generation by Exploring Knowledge Graph](https://aclanthology.org/2020.emnlp-main.90/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
79. [GPT-too: A Language-Model-First Approach for AMR-to-Text Generation](https://aclanthology.org/2020.acl-main.167/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
80. [Generalized Shortest-Paths Encoders for AMR-to-Text Generation](https://aclanthology.org/2020.coling-main.181/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
81. [Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://aclanthology.org/2020.acl-main.640/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
82. [Improving AMR Parsing with Sequence-to-Sequence Pre-training](https://aclanthology.org/2020.emnlp-main.196/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
83. [Improving Text-to-Text Pre-trained Models for the Graph-to-Text Task](https://aclanthology.org/2020.webnlg-1.11/) *— 2020 · Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)*
84. [Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation](https://aclanthology.org/2020.emnlp-main.169/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
85. [Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks](https://aclanthology.org/2020.acl-main.67/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
86. [Multilingual AMR-to-Text Generation](https://aclanthology.org/2020.emnlp-main.231/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
87. [Online Back-Parsing for AMR-to-Text Generation](https://aclanthology.org/2020.emnlp-main.92/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
88. [Penman: An Open-Source Library and Tool for AMR Graphs](https://aclanthology.org/2020.acl-demos.35/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations*
89. [Pushing the Limits of AMR Parsing with Self-Learning](https://aclanthology.org/2020.findings-emnlp.288/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
90. [Structural Information Preserving for Graph-to-Text Generation](https://aclanthology.org/2020.acl-main.712/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
91. [XL-AMR: Enabling Cross-Lingual AMR Parsing with Transfer Learning Techniques](https://aclanthology.org/2020.emnlp-main.195/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
92. [融合目标端句法的AMR-to-Text生成(AMR-to-Text Generation with Target Syntax)](https://aclanthology.org/2020.ccl-1.16/) *— 2020 · Proceedings of the 19th Chinese National Conference on Computational Linguistics*
93. [A Partially Rule-Based Approach to AMR Generation](https://md.mova.elamur.ai/free/en/docs/papers/manning-2019-partially-rule-based-approach-amr/) *— our card · 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop*
94. [A Type-coherent, Expressive Representation as an Initial Step to Language Understanding](https://aclanthology.org/W19-0402/) *— 2019 · Proceedings of the 13th International Conference on Computational Semantics - Long Papers*
95. [AMR Parsing as Sequence-to-Graph Transduction](https://aclanthology.org/P19-1009/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
96. [AMR-to-Text Generation with Cache Transition Systems](https://arxiv.org/abs/1912.01682) *— 2019 · arXiv:1912.01682*
97. [Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation](https://aclanthology.org/D19-5618/) *— 2019 · Proceedings of the 3rd Workshop on Neural Generation and Translation*
98. [Amazon at MRP 2019: Parsing Meaning Representations with Lexical and Phrasal Anchoring](https://aclanthology.org/K19-2013/) *— 2019 · Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning*
99. [Automatic Accuracy Prediction for AMR Parsing](https://aclanthology.org/S19-1024/) *— 2019 · Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)*
100. [Broad-Coverage Semantic Parsing as Transduction](https://aclanthology.org/D19-1392/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*

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