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Jinbao Li

ACL 2026×3ICLR 2026KDD 2026安全评测与基准可解释性推理社会与人本
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0 一作 · 5 篇 · ACL 2026 / ICLR 2026 / KDD 2026

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2026 顶会论文

5
作者位次 #9/10ACL 2026Poster· Natural Language Processing

“ I See What You Did There”: Can Large Vision-Language Models Understand Multimodal Puns?

Naen Xu · Jiayi Sheng · Changjiang Li · Chunyi Zhou · Yuyuan Li · Tianyu Du · Jun Wang · Zhihui Fu · Jinbao Li · Shouling Ji

摘要

Puns are a common form of rhetorical wordplay that exploits polysemy and phonetic similarity to create humor. In multimodal puns, visual and textual elements synergize to ground the literal sense and evoke the figurative meaning simultaneously. Although Vision-Language Models (VLMs) are widely us...

多模态评测与基准推理OpenReview 项目页
作者位次 #10/11ACL 2026Poster· Natural Language Processing

Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors

Rui Yin · Tianxu Han · Naen Xu · Changjiang Li · Ping He · Chunyi Zhou · Jun Wang · Zhihui Fu · Tianyu Du · Jinbao Li · Shouling Ji

摘要

Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines, yet this deployment also enlarges the supply-chain attack surface: adversaries can distribute backdoored checkpoints that behave normally under standard evaluation but jailbreak when a hidden trigger is...

安全可解释性评测与基准OpenReview 项目页
作者位次 #7/8ACL 2026Findings· Findings of ACL

P er M em S afe: Benchmarking Implicit Personalized Safety of Long Horizon Self-Evolving Agents

Hengyu An · Minxi Li · Naen Xu · Chunyi Zhou · Xiaogang Xu · Tianyu Du · Jinbao Li · Shouling Ji

摘要

Self-evolving agents achieve personalization by accumulating user-specific memories over long horizons. This capability, however, introduces novel safety risks, as responses that are generally safe may become harmful in user-specific contexts. Such safety-relevant contexts often emerge implicitly...

安全评测与基准推理OpenReview 项目页

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