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Zexin Li

ACL 2026×2AAAI 2026ECCV 2026RTSS 2026安全效率与系统智能体与工具多模态对齐与偏好
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1 一作 · 5 篇 · ACL 2026 / AAAI 2026 / ECCV 2026 / RTSS 2026

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2026 顶会论文

5
作者位次 #2/5ECCV 2026Poster

VLMSysTrojan: Stealthy System-Aware Backdoor Attacks Against Vision-Language Models

Yezheng Cheng · Zexin Li · Jiaqi Wu · Zhihong Zhang · Simin Chen

安全多模态效率与系统Federated, Continual & Efficient Learning; Model SecurityOpenReview
作者位次 #2/5ACL 2026Poster· Natural Language Processing

N atural S loth: Revisiting Denial-of-Service Attacks on Large Language Models

Yiming Chen · Zexin Li · Xianghu Yue · Robby T. Tan · Haizhou Li

摘要

LLM serving is limited by provider-side resources: longer generations consume more GPU time, increase latency, and reduce throughput in multi-tenant systems. This creates a denial-of-service (DoS) risk, where attackers degrade service by inducing excessive generation. Prior work on LLM DoS primar...

安全智能体与工具效率与系统OpenReview 项目页
作者位次 #3/10ACL 2026Findings· Findings of ACL

H yper E dit: Unlocking Instruction-based Text Editing in LLM s via Hypernetworks

Yiming Zeng · Jinghan Cao · Zexin Li · Wanhao Yu · Zhankai Ye · Dawei Xiang · Ting Hua · Xin Liu · Shangqian Gao · Tingting Yu

摘要

Large Language Models (LLMs) have fundamentally transformed natural language processing (NLP), demonstrating remarkable capabilities across a wide spectrum of tasks. However, when applied to instruction-based text editing, LLMs continue to exhibit some limitations. Different from free-form genera...

对齐与偏好OpenReview 项目页

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