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

1. Paraphrasing as Zero-shot Translation with Feature-guided Diversity Enhancement — 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 — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
3. Ambiguity and Disagreement in Abstract Meaning Representation — 2025 · Proceedings of Context and Meaning: Navigating Disagreements in NLP Annotation
4. Data Drives Unstable Hierarchical Generalization in LMs — 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 — 2025 · arXiv:2506.02018
6. LingConv: An Interactive Toolkit for Controlled Paraphrase Generation with Linguistic Attribute Control — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
7. Linguistically-Controlled Paraphrase Generation — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
8. PAM: Paraphrase AMR-Centric Evaluation Metric — 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 — 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 — 2025 · arXiv:2505.08504
11. Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints — 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 — our card · 2025 · arXiv:2505.03229
13. VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models — 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 — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
15. A Survey of Meaning Representations – From Theory to Practical Utility — 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? — 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 — 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 — 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 — 2023 · arXiv:2305.16635