Linguistically-Controlled Paraphrase Generation
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917108891254784 |
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| author | Elgaar, Mohamed Amiri, Hadi |
| author_facet | Elgaar, Mohamed Amiri, Hadi |
| contents | Controlled paraphrase generation produces paraphrases that preserve meaning while allowing precise control over linguistic attributes of the output. We introduce LingConv, an encoder-decoder framework that enables fine-grained control over 40 linguistic attributes in English. To improve reliability, we introduce a novel inference-time quality control mechanism that iteratively refines attribute embeddings to generate paraphrases that closely match target attributes without sacrificing semantic fidelity. LingConv reduces attribute error by up to 34% over existing models, with the quality control mechanism contributing an additional 14% improvement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_24199 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Linguistically-Controlled Paraphrase Generation Elgaar, Mohamed Amiri, Hadi Computation and Language Controlled paraphrase generation produces paraphrases that preserve meaning while allowing precise control over linguistic attributes of the output. We introduce LingConv, an encoder-decoder framework that enables fine-grained control over 40 linguistic attributes in English. To improve reliability, we introduce a novel inference-time quality control mechanism that iteratively refines attribute embeddings to generate paraphrases that closely match target attributes without sacrificing semantic fidelity. LingConv reduces attribute error by up to 34% over existing models, with the quality control mechanism contributing an additional 14% improvement. |
| title | Linguistically-Controlled Paraphrase Generation |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2410.24199 |