11 citations · 29 across the 14 of their papers we have counts for
9 papers · 1 filter
Is the Future Predictable? Modeling Future Predictability for Reliable Temporal Reasoning
Yongyi Huang, Huaping Zhang, Wenyao Cui +3
Large language models (LLMs) remain unreliable when reasoning about the future. Existing models often overlook the difference among future states, committing to specific answers ev…
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…
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…
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…
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…
A Survey of Quantum-Cognitively Inspired Sentiment Analysis Models
Yaochen Liu, Qiuchi Li, Benyou Wang +2
Quantum theory, originally proposed as a physical theory to describe the motions of microscopic particles, has been applied to various non-physics domains involving human cognition…