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Fei Li

ACL 2026×4AAAI 2026CVPR 2026多模态对齐与偏好安全推理可解释性
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0 一作 · 6 篇 · ACL 2026 / AAAI 2026 / CVPR 2026

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2026 顶会论文

6
作者位次 #6/8ACL 2026Poster· Natural Language Processing

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection

Li Zheng · Yanyi Luo · Hao Fei · Yuzhe Ding · Yujie Huang · Fei Li · Chong Teng · Donghong Ji

摘要

Deception detection is of great significance for ensuring information security and conducting public opinion analysis, with personality factors and emotion cues playing a critical role. However, existing methods lack sample-level dynamic annotations for emotions and personality. In this paper, we...

对齐与偏好安全多模态OpenReview 项目页
作者位次 #4/8ACL 2026Poster· Natural Language Processing

Are Emotion and Rhetoric Neurons in LLM ? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering

Li Zheng · Xin Zhang · Shuyi He · Fei Li · Chong Teng · Jiang-Ming Yang · Donghong Ji · Zhuang Li

摘要

Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models (LLMs). Existing studies mostly rely on external optimizations, lacking in-depth exploration of internal representation mechanisms, thus failing...

可解释性推理数据与预训练OpenReview 项目页
作者位次 #7/7ACL 2026Poster· Natural Language Processing

SHARP : Self-adaptive Harmful Category-aware Prompt Generation for Black-box Jailbreaking

Yingjie Xue · Xingyou Xia · Jun Zhang · Yunbo Cao · Dengpan Ye · Guotong Geng · Fei Li

摘要

Large Language Models (LLMs) have been widely applied in various domains such as education and healthcare, making safety assurance crucial. Jailbreak attacks, a method used in red-teaming, can help evaluate and improve the defensive strategies of LLMs. However, existing jailbreak methods often ov...

安全对齐与偏好强化学习与后训练OpenReview 项目页
作者位次 #7/9ACL 2026Findings· Findings of ACL

Uncertainty-Calibrated Elastic Alignment for Multimodal Sentiment Analysis with Missing Modalities

Kang He · Yuzhe Ding · Rao Fu · Yukang Feng · Kaipeng Zhang · Yiming Liu · Fei Li · Chong Teng · Donghong Ji

摘要

Multimodal sentiment analysis (MSA) in real-world scenarios is often challenged by dynamically missing modalities. Existing methods predominantly rely on deterministic imputation and rigid alignment, which compels the model to overfit noise in ambiguous regions while neglecting the decision shift...

推理对齐与偏好多模态OpenReview 项目页

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