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Wanli Peng

ACL 2026×3AAAI 2026ICLR 2026安全多模态推理检索与知识可解释性
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0 一作 · 5 篇 · ACL 2026 / AAAI 2026 / ICLR 2026

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2026 顶会论文

5
作者位次 #2/5ACL 2026Poster· Natural Language Processing

I m F : Embedding an Implicit Fingerprint in Your Large Language Models

Jiaxuan Wu · Wanli Peng · Hang fu · Xue Yiming · Juan Wen

摘要

Training and serving large language models (LLMs) is resource-intensive, making reliable intellectual property (IP) protection and black-box ownership verification increasingly important.Model fingerprinting enables such verification by injecting a small set of secret query–response behaviors, bu...

推理安全多模态OpenReview 项目页
作者位次 #2/6ACL 2026Poster· Natural Language Processing

Inhibitory Attacks on Backdoor-based Fingerprinting for Large Language Models

Hang fu · Wanli Peng · Yinghan Zhou · Jiaxuan Wu · Juan Wen · Xue Yiming

摘要

The widespread adoption of Large Language Model (LLM) in commercial and research settings has intensified the need for robust intellectual property protection. Backdoor-based LLM fingerprinting has emerged as a promising solution for this challenge. In practical application, the low-cost multi-mo...

安全可解释性检索与知识OpenReview 项目页
作者位次 #3/6ACL 2026Findings· Findings of ACL

SLIP : Soft Label Mechanism and Key-Extraction-Guided C o T -based Defense Against Instruction Backdoor in API s

Wu Zhengxian · Juan Wen · Wanli Peng · Haowei Chang · Yinghan Zhou · Xue Yiming

摘要

Customized Large Language Model (LLM) agents face a critical security threat from black-box instruction backdoors, where malicious behaviors are covertly injected through hidden system instructions. Although existing prompt-based defenses can often detect poisoned inputs, they generally fail to r...

推理安全智能体与工具OpenReview 项目页

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