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# Who cites «AMR-to-text Generation with Synchronous Node Replacement Grammar»

30 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/song-2017-amr-text-generation-synchronous-node/)

1. [Semantic Bridge: Universal Multi-Hop Question Generation via AMR-Driven Graph Synthesis](https://arxiv.org/abs/2508.10013) *— 2025 · arXiv:2508.10013*
2. [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*
3. [Exploring a POS-based Two-stage Approach for Improving Low-Resource AMR-to-Text Generation](https://aclanthology.org/2022.gem-1.49/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
4. [Latent Tree Decomposition Parsers for AMR-to-Text Generation](https://arxiv.org/abs/2108.12304) *— 2021 · arXiv:2108.12304*
5. [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*
6. [AMR Similarity Metrics from Principles](https://aclanthology.org/2020.tacl-1.34/) *— 2020*
7. [AMR-To-Text Generation with Graph Transformer](https://aclanthology.org/2020.tacl-1.2/) *— 2020 · Transactions of the Association for Computational Linguistics*
8. [DART: Open-Domain Structured Data Record to Text Generation](https://arxiv.org/abs/2007.02871) *— 2020 · arXiv:2007.02871*
9. [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*
10. [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*
11. [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)*
12. [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*
13. [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)*
14. [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*
15. [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*
16. [Contextualization of Morphological Inflection](https://aclanthology.org/N19-1203/) *— 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)*
17. [Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://aclanthology.org/Q19-1019/) *— 2019 · Transactions of the Association for Computational Linguistics*
18. [Factorising AMR generation through syntax](https://md.mova.elamur.ai/free/en/docs/papers/cao-2019-factorising-amr-generation-through-syntax/) *— our card · 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)*
19. [Generating Text from Anonymised Structures](https://aclanthology.org/W19-8614/) *— 2019 · Proceedings of the 12th International Conference on Natural Language Generation*
20. [Modeling Graph Structure in Transformer for Better AMR-to-Text Generation](https://aclanthology.org/D19-1548/) *— 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)*
21. [Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes](https://aclanthology.org/D19-1638/) *— 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)*
22. [A Graph-to-Sequence Model for AMR-to-Text Generation](https://aclanthology.org/P18-1150/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Abstract Meaning Representation for Multi-Document Summarization](https://aclanthology.org/C18-1101/) *— 2018 · Proceedings of the 27th International Conference on Computational Linguistics*
24. [Graph-to-Sequence Learning using Gated Graph Neural Networks](https://aclanthology.org/P18-1026/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
25. [Towards AMR-BR: A SemBank for Brazilian Portuguese Language](https://aclanthology.org/L18-1157/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
26. [Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation](https://md.mova.elamur.ai/free/en/docs/papers/ferreira-2017-linguistic-realisation-as-machine-translation/) *— our card · 2017 · Proceedings of the 10th International Conference on Natural Language Generation*
27. [Transition-Based Generation from Abstract Meaning Representations](https://arxiv.org/abs/1707.07591) *— 2017 · arXiv:1707.07591*
28. cabezudo-2019-natural-language-generation-recently-learned
29. lo-2022-semantic-composition-pshrg-derivation-tree
30. ye-2018-language-generation-dag-transduction
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