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Yuchen Li

ACL 2026×7AAAI 2026×3ICLR 2026KDD 2026推理效率与系统评测与基准强化学习与后训练检索与知识
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1 一作 · 12 篇 · ACL 2026 / AAAI 2026 / ICLR 2026 / KDD 2026

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2026 顶会论文

12
作者位次 #5/7ACL 2026Poster· Natural Language Processing

R eason R ank: Empowering Passage Ranking with Strong Reasoning Ability

Wenhan Liu · xinyu ma · Weiwei Sun · Yutao Zhu · Yuchen Li · Dawei Yin · Zhicheng Dou

摘要

Large Language Model (LLM) based listwise ranking has shown superior performance in many passage ranking tasks. With the development of Large Reasoning Models (LRMs), many studies have demonstrated that step-by-step reasoning during test-time helps improve listwise ranking performance. However, d...

强化学习与后训练推理效率与系统OpenReview 项目页
作者位次 #5/10ACL 2026Findings· Findings of ACL

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

Jingyu Peng · Maolin WANG · Nan Wang · Jiatong Li · Yuchen Li · Yuyang Ye · an Jiaotong University) · an Jiaotong University) · Kai Zhang · an Jiaotong University)

摘要

Despite substantial advancements in aligning LLMs with human values, current safety mechanisms remain susceptible to jailbreak attacks. We attribute this vulnerability to the distributional discrepancies between alignment-oriented prompts and malicious prompts. To investigate this, and drawing in...

安全多语言与语言学评测与基准OpenReview 项目页
作者位次 #7/8ACL 2026Findings· Findings of ACL

On the Representation Geometry of L o RA Model Merging

Chenyang Lu · Jiaru Li · Jinman Zhao · Xinran Chen · Yining Wang · Renyi Cai · Yuchen Li · Chao He

摘要

Low-Rank Adaptation (LoRA) is widely used for parameter-efficient fine-tuning, yet merging multiple task-specific LoRA updates without additional training remains challenging. Most existing LoRA merging methods rely on SVD-based alignment, which emphasizes globally shared structure across tasks....

效率与系统对齐与偏好可解释性OpenReview 项目页
作者位次 #4/7ACL 2026Findings· Findings of ACL

Agentic- R : Learning to Retrieve for Agentic Search

Wenhan Liu · xinyu ma · Yutao Zhu · Yuchen Li · Daiting Shi · Dawei Yin · Zhicheng Dou

摘要

Agentic search has recently emerged as a powerful paradigm, where an agent interleaves multi-step reasoning with on-demand retrieval to solve complex questions. Despite its success, how to design a retriever for agentic search remains largely underexplored. Existing search agents typically rely o...

检索与知识评测与基准推理OpenReview 项目页
作者位次 #7/12ACL 2026Findings· Findings of ACL

U ni C reative: Unifying Long-form Logic and Short-form Sparkle via Reference-Free Reinforcement Learning

Xiaolong Wei · Zerun Zhu · Simin Niu · Xingyu Zhang · Peiying Yu · Changxuan Xiao · Yuchen Li · Jicheng Yang · Zhejun Zhao · Chong Meng · Long Xia · Daiting Shi

摘要

A fundamental challenge in creative writing lies in reconciling the inherent tension between maintaining global coherence in long-form narratives and preserving local expressiveness in short-form texts. While long-context generation necessitates explicit macroscopic planning, short-form creativit...

对齐与偏好强化学习与后训练推理OpenReview 项目页
作者位次 #5/12ACL 2026Findings· Findings of ACL

Dr. Assistant: Enhancing Clinical Diagnostic Inquiry via Structured Diagnostic Reasoning Data and Reinforcement Learning

Yue Guo · Fanfu Wang · Jianwei Lv · Xincheng Shi · Yuchen Li · Youya Wang · Yunsheng Zeng · Yujing Liu · Yunhao Qiao · Gen Li · Junfeng Wang · Bo Yuan

摘要

Clinical Decision Support Systems (CDSSs) provide reasoning and inquiry guidance for physicians, yet they face notable challenges, including high maintenance costs and low generalization capability.Recently, Large Language Models (LLMs) have been widely adopted in healthcare due to their extensiv...

社会与人本推理强化学习与后训练OpenReview 项目页
作者位次 #6/9ACL 2026Findings· Findings of ACL

Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models

Can Xu · Lingyong Yan · Jiayi Wu · Haosen Wang · Shuaiqiang Wang · Yuchen Li · Jizhou Huang · Dawei Yin · Xiang Li

摘要

Recent advances in synergizing large reasoning models (LRMs) with retrieval-augmented generation (RAG) have shown promising results, yet two critical challenges remain: (1) reasoning models typically operate from a single, unchallenged perspective, limiting their ability to conduct deep, self-cor...

推理检索与知识安全OpenReview 项目页

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