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Zhi Zheng

ACL 2026×2SIGIR 2026推理智能体与工具检索与知识安全数据与预训练
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0 一作 · 3 篇 · ACL 2026 / SIGIR 2026

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2026 顶会论文

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

VIGIL : Defending LLM Agents Against Tool-Stream Injection via Verify-Before-Commit

Junda Lin · Zhaomeng Zhou · Zhi Zheng · Shuochen Liu · an Jiaotong University) · Yong Chen · Enhong Chen (University of Science and Technology of China &amp

摘要

LLM agents operating in open environments face escalating risks from indirect prompt injection, particularly within the tool stream where manipulated metadata and runtime feedback hijack execution flow. Existing defenses encounter a critical dilemma as advanced models prioritize injected rules du...

安全推理智能体与工具OpenReview 项目页
作者位次 #2/8ACL 2026Poster· Natural Language Processing

Memory-Augmented LLM -based Multi-Agent System for Automated Feature Generation on Tabular Data

FengXian Dong · Zhi Zheng · Xiao Han · Wei Chen · Jingqing Ruan · an Jiaotong University) · Yong Chen · Enhong Chen (University of Science and Technology of China &amp

摘要

Automated feature generation extracts informative features from raw tabular data without manual intervention and is crucial for accurate, generalizable machine learning. Traditional methods rely on predefined operator libraries and cannot leverage task semantics, limiting their ability to produce...

智能体与工具数据与预训练检索与知识OpenReview 项目页
作者位次 #3/5SIGIR 2026Oral· Information Retrieval (Full)

STRIDE: Strategic Iterative Decision-Making for Retrieval-Augmented Multi-Hop Question Answering

Wei Chen · Lili Zhao · Zhi Zheng · Huijun Hou · an Jiaotong University)

摘要

Multi-hop question answering (MHQA) enables accurate answers to complex queries by retrieving and reasoning over evidence dispersed across multiple documents. Existing MHQA approaches mainly rely on iterative retrieval-augmented generation, which suffer from the following two major issues. On one...

推理检索与知识效率与系统OpenReview

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