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Chengkun Cai

ACL 2026×2安全多模态评测与基准理论与学习动力学可解释性
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #5/11ACL 2026Poster· Natural Language Processing

S afe MT : Multi-turn Safety for Multimodal Language Models

Han Zhu · Juntao Dai · Jiaming Ji · Haoran Li · Chengkun Cai · Pengcheng Wen · Chi-Min Chan · Boyuan Chen · Yaodong Yang · Sirui Han · Yike Guo

摘要

With the widespread use of multi-modal Large Language models (MLLMs), safety issues have become a growing concern. Multi-turn dialogues, which are more common in everyday interactions, pose a greater risk than single prompts; however, existing benchmarks do not adequately consider this situation....

安全多模态评测与基准OpenReview 项目页
作者位次 #2/10ACL 2026Findings· Findings of ACL

BCL : B ayesian In-Context Learning Framework for Information Extraction

Haoliang Liu · Chengkun Cai · Xu Zhao · Han Zhu · Shizhou Huang · Xinglin Zhang · Tao Chen · Jenq-Neng Hwang · Zhang Huaping · Lei Li

摘要

Existing information extraction (IE) tasks increasingly adopt in-context learning (ICL) with large language models. However, current approaches either show inconsistent performance across model scales or lack systematic optimization and generalizability. Building on this, we propose BCL-IE (Bayes...

理论与学习动力学可解释性OpenReview 项目页

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