Improving LLMs' Learning for Coreference Resolution
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909787177877504 |
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| author | Gan, Yujian Liang, Yuan Lin, Yanni Yu, Juntao Poesio, Massimo |
| author_facet | Gan, Yujian Liang, Yuan Lin, Yanni Yu, Juntao Poesio, Massimo |
| contents | Coreference Resolution (CR) is crucial for many NLP tasks, but existing LLMs struggle with hallucination and under-performance. In this paper, we investigate the limitations of existing LLM-based approaches to CR-specifically the Question-Answering (QA) Template and Document Template methods and propose two novel techniques: Reversed Training with Joint Inference and Iterative Document Generation. Our experiments show that Reversed Training improves the QA Template method, while Iterative Document Generation eliminates hallucinations in the generated source text and boosts coreference resolution. Integrating these methods and techniques offers an effective and robust solution to LLM-based coreference resolution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_11466 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Improving LLMs' Learning for Coreference Resolution Gan, Yujian Liang, Yuan Lin, Yanni Yu, Juntao Poesio, Massimo Computation and Language Coreference Resolution (CR) is crucial for many NLP tasks, but existing LLMs struggle with hallucination and under-performance. In this paper, we investigate the limitations of existing LLM-based approaches to CR-specifically the Question-Answering (QA) Template and Document Template methods and propose two novel techniques: Reversed Training with Joint Inference and Iterative Document Generation. Our experiments show that Reversed Training improves the QA Template method, while Iterative Document Generation eliminates hallucinations in the generated source text and boosts coreference resolution. Integrating these methods and techniques offers an effective and robust solution to LLM-based coreference resolution. |
| title | Improving LLMs' Learning for Coreference Resolution |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2509.11466 |