5 papers
Visual Room 2.0: Seeing is Not Understanding for MLLMs
Haokun Li, Yazhou Zhang, Jizhi Ding +2
Can multi-modal large language models (MLLMs) truly understand what they can see? Extending Searle's Chinese Room into the multi-modal domain, this paper proposes the Visual Room a…
Seeing is Not Understanding: A Benchmark on Perception-Cognition Disparities in Large Language Models
Haokun Li, Yazhou Zhang, Jizhi Ding +2
With the rapid advancement of Multimodal Large Language Models (MLLMs), they have demonstrated exceptional capabilities across a variety of vision-language tasks. However, current…
Are MLMs Trapped in the Visual Room?
Yazhou Zhang, Chunwang Zou, Qimeng Liu +6
Can multi-modal large models (MLMs) that can ``see'' an image be said to ``understand'' it? Drawing inspiration from Searle's Chinese Room, we propose the \textbf{Visual Room} argu…
NurValues: Real-World Nursing Values Evaluation for Large Language Models in Clinical Context
Ben Yao, Qiuchi Li, Yazhou Zhang +4
While LLMs have demonstrated medical knowledge and conversational ability, their deployment in clinical practice raises new risks: patients may place greater trust in LLM-generated…
Beyond Single-Sentence Prompts: Upgrading Value Alignment Benchmarks with Dialogues and Stories
Yazhou Zhang, Qimeng Liu, Qiuchi Li +2
Evaluating the value alignment of large language models (LLMs) has traditionally relied on single-sentence adversarial prompts, which directly probe models with ethically sensitive…