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20242026
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cs.CL2026

Why Did Apple Fall: Evaluating Curiosity in Large Language Models

Haoyu Wang, Sihang Jiang, Yuyan Chen +4

Curiosity serves as a pivotal conduit for human beings to discover and learn new knowledge. Recent advancements of large language models (LLMs) in natural language processing have…

cs.CL2024

Do Large Language Models have Problem-Solving Capability under Incomplete Information Scenarios?

Yuyan Chen, Tianhao Yu, Yueze Li +4

The evaluation of the problem-solving capability under incomplete information scenarios of Large Language Models (LLMs) is increasingly important, encompassing capabilities such as…

cs.CL2024

EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models

Yuyan Chen, Hao Wang, Songzhou Yan +4

Emotional intelligence in large language models (LLMs) is of great importance in Natural Language Processing. However, the previous research mainly focus on basic sentiment analysi…

cs.CL2024

Recent Advancement of Emotion Cognition in Large Language Models

Yuyan Chen, Yanghua Xiao

Emotion cognition in large language models (LLMs) is crucial for enhancing performance across various applications, such as social media, human-computer interaction, and mental hea…

cs.CL2024

Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models

Yuyan Chen, Qiang Fu, Yichen Yuan +6

Large Language Models (LLMs) have gained widespread adoption in various natural language processing tasks, including question answering and dialogue systems. However, a major drawb…

cs.CL2024

MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization

Yuyan Chen, Zhihao Wen, Ge Fan +6

Prompt engineering, as an efficient and effective way to leverage Large Language Models (LLM), has drawn a lot of attention from the research community. The existing research prima…