Papers by Xingyu Bian
MedQA-CS: Objective Structured Clinical Examination (OSCE)-Style Benchmark for Evaluating LLM Clinical Skills (2026.eacl-long)
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Zonghai Yao, Zihao Zhang, Chaolong Tang, Xingyu Bian, Youxia Zhao, Zhichao Yang, Junda Wang, Huixue Zhou, Won Seok Jang, Feiyun Ouyang, Hong Yu
| Challenge: | Current clinical LLM benchmarks fail to evaluate advanced clinical skills in AI and large language models (LLMs). |
| Approach: | They propose a framework to evaluate large language models (LLMs) using two instruction-following tasks designed to reflect real clinical scenarios. |
| Outcome: | The proposed framework evaluates LLMs through two instruction-following tasks designed to reflect real clinical scenarios. |
On Attention Redundancy: A Comprehensive Study (2021.naacl-main)
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| Challenge: | Attention redundancy has been observed among attention heads but has not been deeply studied in the literature. |
| Approach: | They propose a multi-layer multi-head self-attention mechanism which is widely applied in modern neural language models. |
| Outcome: | The proposed model is useful for interpretation and model compression. |
Training on Lexical Resources (2022.lrec-1)
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| Challenge: | In this paper, we fine-tune pretrained deep nets such as BERT and ERNIE . at inference time, these nets can be used to distinguish synonyms from antonyms . |
| Approach: | They propose to use lexical resources to fine-tune pretrained deep nets such as BERT and ERNIE to distinguish synonyms from antonyms. |
| Outcome: | The proposed method can be applied to multiword expressions, out of vocabulary words, morphological variants and more. |