3 papers
cs.CL2026
Self-Evolving Deep Research via Joint Generation and Evaluation
Han Zhu, Chengkun Cai, Yuanfeng Song +3
Large Language Models (LLMs) have become increasingly adopted in daily applications, with deep research standing out as a particularly important capability. Unlike traditional ques…
cs.CL2026
AMSafety: Towards Data Efficient Alignment of Multi-modal Multi-turn Safety for MLLMs
Han Zhu, Jiale Chen, Chengkun Cai +8
Multi-modal Large Language Models (MLLMs) are increasingly deployed in interactive applications. However, their safety vulnerabilities become pronounced in multi-turn multi-modal s…
cs.CL2025
SafeMT: Multi-turn Safety for Multimodal Language Models
Han Zhu, Juntao Dai, Jiaming Ji +8
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 interacti…