Papers by Varun Iyer
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation (2023.acl-long)
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| Challenge: | Paraphrase generation is a long-standing task in natural language processing (NLP). |
| Approach: | They propose to generate large-scale syntactically diverse paraphrase datasets by abstract meaning representation back-translation. |
| Outcome: | The proposed dataset is syntactically more diverse than existing datasets while maintaining good semantic similarity. |
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations (2022.findings-emnlp)
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| Challenge: | Existing approaches to syntactically controlled paraphrase generation require annotated paraphrase pairs for training and are costly to extend to new domains. |
| Approach: | They propose to leverage Abstract Meaning Representations (AMR) to improve the performance of unsupervised syntactically controlled paraphrase generation. |
| Outcome: | The proposed model generates more accurate syntactically controlled paraphrases, both quantitatively and qualitatively, compared to the existing unsupervised approaches. |