11 citations · 31 across the 12 of their papers we have counts for
12 papers
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…
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…
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…
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…
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…
SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Yazhou Zhang, Chunwang Zou, Zheng Lian +2
In the era of large language models (LLMs), the task of ``System I''~-~the fast, unconscious, and intuitive tasks, e.g., sentiment analysis, text classification, etc., have been ar…
Is Sarcasm Detection A Step-by-Step Reasoning Process in Large Language Models?
Ben Yao, Yazhou Zhang, Qiuchi Li +1
Elaborating a series of intermediate reasoning steps significantly improves the ability of large language models (LLMs) to solve complex problems, as such steps would evoke LLMs to…
WundtGPT: Shaping Large Language Models To Be An Empathetic, Proactive Psychologist
Chenyu Ren, Yazhou Zhang, Daihai He +1
Large language models (LLMs) are raging over the medical domain, and their momentum has carried over into the mental health domain, leading to the emergence of few mental health LL…
Pushing The Limit of LLM Capacity for Text Classification
Yazhou Zhang, Mengyao Wang, Chenyu Ren +4
The value of text classification's future research has encountered challenges and uncertainties, due to the extraordinary efficacy demonstrated by large language models (LLMs) acro…
DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversations
Yazhou Zhang, Mengyao Wang, Youxi Wu +4
Large language models (LLMs) and their variants have shown extraordinary efficacy across numerous downstream natural language processing (NLP) tasks, which has presented a new visi…