Papers by Chun Peng
Improving Automatic Evaluation of Large Language Models (LLMs) in Biomedical Relation Extraction via LLMs-as-the-Judge (2025.acl-long)
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| Challenge: | Large Language Models generate human-like text, making them unreliable for biomedical relation extraction tasks. |
| Approach: | They propose to use Large Language Models as judges to evaluate biomedical relation extraction . they propose structured output formatting for LLM-generated responses that helps LLMs improve their performance by 15%. |
| Outcome: | The proposed method improves LLM-Judges' performance by 15% . it is cheaper and more efficient than human evaluation metrics, the authors say . |
Paraphrase Generation as Unsupervised Machine Translation (2022.coling-1)
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| Challenge: | Existing methods for paraphrase generation rely on labeled datasets or are limited in narrow domains. |
| Approach: | They propose a paradigm for paraphrase generation by treating the task as unsupervised machine translation based on pairs of unlabeled monolingual sentences. |
| Outcome: | The proposed paradigm can generate paraphrases on a large unlabeled monolingual corpus without relying on bilingual sentence pairs. |