Papers by Changxuan Sun
FaStFact: Faster, Stronger Long-Form Factuality Evaluations in LLMs (2025.findings-emnlp)
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Yingjia Wan, Haochen Tan, Xiao Zhu, Xinyu Zhou, Zhiwei Li, Qingsong Lv, Changxuan Sun, Jiaqi Zeng, Yi Xu, Jianqiao Lu, Yinhong Liu, Zhijiang Guo
| Challenge: | Prior evaluation pipelines fail to evaluate factuality of long-form LLMs due to inefficiency and costly human assessment. |
| Approach: | They propose a fast and strong evaluation pipeline that can evaluate factuality of long-form LLMs . they propose 'faStFact' to reduce cost of web searching and inference calling . |
| Outcome: | The proposed evaluation pipeline achieves highest alignment with human evaluation and efficiency among existing baselines. |
Two Issues with Chinese Spelling Correction and A Refinement Solution (2024.acl-short)
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| Challenge: | Existing models contain many spelling errors, resulting in performance bottlenecks and performance issues. |
| Approach: | They propose to fix the SIGHAN datasets and re-evaluate four representative Chinese Spelling Correction models using the fixed datasets. |
| Outcome: | The proposed model improves the models in all metrics by notable margins. |