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Deyu Zhou

ACL 2026×5智能体与工具推理检索与知识效率与系统评测与基准
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0 一作 · 5 篇 · ACL 2026

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2026 顶会论文

5
作者位次 #6/6ACL 2026Poster· Natural Language Processing

When KV Cache Reuse Fails in Multi-Agent Systems: Cross-Candidate Interaction is Crucial for LLM Judges

Sichu Liang · Zhenglin Wang · Chujiajia · Pengfei Xia · Hui Zang · Deyu Zhou

摘要

Multi-agent LLM systems routinely generate multiple candidate responses that are aggregated by an LLM judge. To reduce the dominant prefill cost in such pipelines, recent work advocates KV cache reuse across partially shared contexts and reports substantial speedups for generation agents. In this...

效率与系统智能体与工具评测与基准OpenReview 项目页
作者位次 #4/5ACL 2026Poster· Natural Language Processing

Beyond Meta-Reasoning: Metacognitive Consolidation for Self-Improving LLM Reasoning

Ziqing Zhuang · Linhai Zhang · Jiasheng Si · Deyu Zhou · Yulan He

摘要

Large language models (LLMs) have demonstrated strong reasoning capabilities, and as existing approaches for enhancing LLM reasoning continue to mature, increasing attention has shifted toward meta-reasoning as a promising direction for further improvement. However, most existing meta-reasoning m...

推理可解释性强化学习与后训练OpenReview 项目页
作者位次 #7/8ACL 2026Poster· Natural Language Processing

Beyond Static Artifacts: An Evolutionary Framework for Synthetic Claim Generation

Yeqing Teng · Jiasheng Si · Shuxia Lin · Linhai Zhang · Weiyu Zhang · Wenpeng Lu (Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences) · Deyu Zhou · Xiaoming Wu

摘要

With the generative capabilities of large language models (LLMs) reshaping the information ecosystem, the concern with the sociological validity of claim detection benchmarks is increasing. Current claim detection benchmarks predominantly treat claims as static textual artifacts, overlooking the...

智能体与工具数据与预训练社会与人本OpenReview 项目页
作者位次 #5/5ACL 2026Findings· Findings of ACL

MA ^{2} P : A Meta-Cognitive Autonomous Intelligent Agents Framework for Complex Persuasion

Dingyi Zhang · Ziqing Zhuang · Linhai Zhang · Ziyang Gao · Deyu Zhou

摘要

Persuasive dialogue generation plays a vital role in decision-making, negotiation, counseling, and behavior change, yet it remains a challenging problem. In complex persuasion where the persuadee’s internal states are not expressed clearly, the persuader must interpret responses, infer the persua...

推理智能体与工具检索与知识OpenReview 项目页
作者位次 #3/3ACL 2026Findings· Findings of ACL

Let the Comments Speak: A Multi-Agent Framework based on Large Language Model for Comment-Guided Code Refactoring

Zixuan Wang · Wutong Yu · Deyu Zhou

摘要

Code refactoring is essential for software maintainability, yet current Large Language Model (LLM) based frameworks primarily focus on syntax and neglect the vital semantic signals in code comments. As pointed out in Fowler’s refactoring theory, explanatory comments function as semantic anchors t...

检索与知识智能体与工具代码OpenReview 项目页

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