--- title: "Who cites ParaAMR: A Large-Scale Syntactically Diverse…" description: "The papers of the Elamur Research library that cite «ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation», found in…" canonical: "https://research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ParaAMR: A Large-Scale Syntactically Diverse…](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/) / cited by # Who cites «ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation» 19 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/) 1. [Paraphrasing as Zero-shot Translation with Feature-guided Diversity Enhancement](https://aclanthology.org/2026.acl-long.783/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)* 2. [“Emphasizing the Commendable”: A Study of Homogenized Transitive Verb Constructions in Machine Generated Peer Reviews](https://aclanthology.org/2026.lrec-1.836/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference* 3. [Ambiguity and Disagreement in Abstract Meaning Representation](https://aclanthology.org/2025.comedi-1.14/) *— 2025 · Proceedings of Context and Meaning: Navigating Disagreements in NLP Annotation* 4. [Data Drives Unstable Hierarchical Generalization in LMs](https://aclanthology.org/2025.emnlp-main.593/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing* 5. [Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked Data](https://arxiv.org/abs/2506.02018) *— 2025 · arXiv:2506.02018* 6. [LingConv: An Interactive Toolkit for Controlled Paraphrase Generation with Linguistic Attribute Control](https://aclanthology.org/2025.emnlp-demos.4/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations* 7. [Linguistically-Controlled Paraphrase Generation](https://aclanthology.org/2025.findings-emnlp.1137/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025* 8. [PAM: Paraphrase AMR-Centric Evaluation Metric](https://aclanthology.org/2025.findings-acl.879/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025* 9. [Reassessing Graph Linearization for Sequence-to-sequence AMR Parsing: On the Advantages and Limitations of Triple-Based](https://aclanthology.org/2025.insights-1.3/) *— 2025 · The Sixth Workshop on Insights from Negative Results in NLP* 10. [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* 11. [Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints](https://aclanthology.org/2025.acl-short.79/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)* 12. [Survey of Abstract Meaning Representation: Then, Now, Future](https://md.research.elamur.ai/free/en/papers/mansouri-2025-survey-abstract-meaning-representation-then/) *— our card · 2025 · arXiv:2505.03229* 13. [VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models](https://aclanthology.org/2025.naacl-long.311/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)* 14. [A Survey of AMR Applications](https://aclanthology.org/2024.emnlp-main.390/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing* 15. [A Survey of Meaning Representations – From Theory to Practical Utility](https://aclanthology.org/2024.naacl-long.159/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)* 16. [How Far Can We Extract Diverse Perspectives from Large Language Models?](https://aclanthology.org/2024.emnlp-main.306/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing* 17. [Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model](https://aclanthology.org/2024.naacl-long.250/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)* 18. [The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text](https://aclanthology.org/2024.findings-naacl.228/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024* 19. [Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing](https://arxiv.org/abs/2305.16635) *— 2023 · arXiv:2305.16635*