activity
20242026
collaborators

9 papers

cs.AI2026

Every Picture Tells a Dangerous Story: Memory-Augmented Multi-Agent Jailbreak Attacks on VLMs

Jianhao Chen, Shiqin Wang, Haoyang Chen +4

Vision-Language Models (VLMs) expand the attack surface of safety-aligned systems by coupling visual perception with text generation. Existing multimodal jailbreak attacks primaril…

cs.CL2026

ContiGuard: A Framework for Continual Toxicity Detection Against Evolving Evasive Perturbations

Hankun Kang, Xin Miao, Jianhao Chen +5

Toxicity detection mitigates the dissemination of toxic content (e.g., hateful comments, posts, and messages within online social actions) to safeguard a healthy online social envi…

cs.AI2025

Can a Small Model Learn to Look Before It Leaps? Dynamic Learning and Proactive Correction for Hallucination Detection

Zepeng Bao, Shen Zhou, Qiankun Pi +5

Hallucination in large language models (LLMs) remains a critical barrier to their safe deployment. For hallucination detection to be practical in real-world scenarios, the use of e…

cs.CR2025

CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations

Xiaohu Li, Yunfeng Ning, Zepeng Bao +3

Security alignment enables the Large Language Model (LLM) to gain the protection against malicious queries, but various jailbreak attack methods reveal the vulnerability of this se…

cs.AI2025

RAJ-PGA: Reasoning-Activated Jailbreak and Principle-Guided Alignment Framework for Large Reasoning Models

Jianhao Chen, Mayi Xu, Haoyang Chen +6

Large Reasoning Models (LRMs) face a distinct safety vulnerability: their internal reasoning chains may generate harmful content even when the final output appears benign. To addre…

cs.LG2025

NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs

Birong Pan, Jianhao Chen, Mayi Xu +4

Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, current techniques fundamentally suffer…

cs.AI2025

Aligning VLM Assistants with Personalized Situated Cognition

Yongqi Li, Shen Zhou, Xiaohu Li +9

Vision-language models (VLMs) aligned with general human objectives, such as being harmless and hallucination-free, have become valuable assistants of humans in managing visual tas…

cs.CL2025

Reasoning based on symbolic and parametric knowledge bases: a survey

Mayi Xu, Yunfeng Ning, Yongqi Li +10

Reasoning is fundamental to human intelligence, and critical for problem-solving, decision-making, and critical thinking. Reasoning refers to drawing new conclusions based on exist…

cs.CR2024

Toxicity Detection towards Adaptability to Changing Perturbations

Hankun Kang, Jianhao Chen, Yongqi Li +5

Toxicity detection is crucial for maintaining the peace of the society. While existing methods perform well on normal toxic contents or those generated by specific perturbation met…