2 citations · 2 across the 4 of their papers we have counts for
10 papers
Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection
Yazhou Zhang, Chunwang Zou, Bo Wang +2
Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many downstream NLP tasks, growing evide…
Edu-Values: Towards Evaluating the Chinese Education Values of Large Language Models
Peiyi Zhang, Yazhou Zhang, Bo Wang +3
In this paper, we present Edu-Values, the first Chinese education values evaluation benchmark that includes seven core values: professional philosophy, teachers' professional ethic…
TextReasoningBench: Does Reasoning Really Improve Text Classification in Large Language Models?
Xinyu Guo, Yazhou Zhang, Jing Qin
Eliciting explicit, step-by-step reasoning traces from large language models (LLMs) has emerged as a dominant paradigm for enhancing model capabilities. Although such reasoning str…
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…
Commander-GPT: Fully Unleashing the Sarcasm Detection Capability of Multi-Modal Large Language Models
Yazhou Zhang, Chunwang Zou, Bo Wang +1
Sarcasm detection, as a crucial research direction in the field of Natural Language Processing (NLP), has attracted widespread attention. Traditional sarcasm detection tasks have t…
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…