3 papers
cs.CV2026
Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment
Zhixue Song, Boyan Han, Yiwei Wang +1
Recent advancements in visual context compression enable MLLMs to process ultra-long contexts efficiently by rendering text into images. However, we identify a critical vulnerabili…
cs.AI2026
DIVE: Scaling Diversity in Agentic Task Synthesis for Generalizable Tool Use
Aili Chen, Chi Zhang, Junteng Liu +11
Recent work synthesizes agentic tasks for post-training tool-using LLMs, yet robust generalization under shifts in tasks and toolsets remains an open challenge. We trace this britt…
cs.SE2026
On the Difficulty of Selecting Few-Shot Examples for Effective LLM-based Vulnerability Detection
Md Abdul Hannan, Ronghao Ni, Chi Zhang +3
Large language models (LLMs) have demonstrated impressive capabilities across a wide range of coding tasks, including summarization, translation, completion, and code generation. D…