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cs.CL2026
Asking What a Director Sees Can Change What Vision-Language Models Choose
Jiaxuan Guo, Xingyu Ren, Kejia Zhang +3
Vision-language models are now routinely tested on theory of mind: whether they can work out what another person sees, knows, and means. A common design asks the model to report th…
cs.CL2026
PerspectiveGap: A Benchmark for Multi-Agent Orchestration Prompting
Youran Sun, Xingyu Ren, Kejia Zhang +2
Real-world LLM applications are moving beyond single-agent workflows toward orchestrated multi-agent systems, yet current models still struggle to determine what each sub-agent nee…
cs.CL2026
DeepSight: An All-in-One LM Safety Toolkit
Bo Zhang, Jiaxuan Guo, Lijun Li +17
As the development of Large Models (LMs) progresses rapidly, their safety is also a priority. In current Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) s…