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Qi Ye

ACL 2026×3评测与基准社会与人本多模态数据与预训练推理
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0 一作 · 3 篇 · ACL 2026

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2026 顶会论文

3
作者位次 #6/7ACL 2026Poster· Natural Language Processing

Tiny Scales, Great Challenges: The Limits of Multimodal LLM s in Scale Recognition

Jihang Jin · Ronghao Chen · Hao Zhang · Ziyan Liu · Huacan Wang · Qi Ye · Jingping Liu

摘要

Visual scale recognition is a fundamental aspect for humans to perceive physical quantities in the real world, and it is crucial for enabling human-like intelligence in multimodal large language models (MLLMs). However, existing benchmarks typically focus on a single type of quantity (e.g., time)...

多模态评测与基准数据与预训练OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

Travel on the ICD Tree: Benchmarking Agentic Reasoning for ICD Coding from C hinese Electronic Medical Records

Xinjie Xu · Yongqi Fan · Shuang-shuang Chen · Qi Ye · Weibin Guo · Xinxuan Hu

摘要

Accurate International Classification of Diseases (ICD) coding is crucial for hospital management and healthcare data governance. In clinical practice, straightforward cases can often be matched directly to ICD codes via diagnostic text, establishing retrieval-based methods as the baseline. More...

社会与人本推理评测与基准OpenReview 项目页
作者位次 #3/9ACL 2026Findings· Findings of ACL

Experience is the Teacher: Reusing Atomic Thoughts from LLM s to Improve Medical Dialogue

Guangya Yu · Hui Luo · Qi Ye · Ruihui Hou · Weiyan Zhang · Mingxi Shang · Xuanwu Li · ChunMing Wang · Tong Ruan

摘要

With the remarkable performance of large language models (LLMs) in medicine, particularly their ability to support clinical decision-making in medical dialogues, a key limitation remains: the static reasoning patterns derived from human expert experience are often inadequate for the dynamic and d...

社会与人本强化学习与后训练代码OpenReview 项目页

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