5 citations · 10 across the 8 of their papers we have counts for
9 papers
Enhancing Multimodal In-Context Learning via Inductive-Deductive Reasoning
Haoyu Wang, Haonan Wang, Yuyan Chen +5
In-context learning (ICL) allows large models to adapt to tasks using a few examples, yet its extension to vision-language models (VLMs) remains fragile. Our analysis reveals that…
Thinking with Constructions: A Benchmark and Policy Optimization for Visual-Text Interleaved Geometric Reasoning
Haokun Zhao, Wanshi Xu, Haidong Yuan +3
Geometric reasoning inherently requires "thinking with constructions" -- the dynamic manipulation of visual aids to bridge the gap between problem conditions and solutions. However…
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…
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying +9
Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful ou…
HOTVCOM: Generating Buzzworthy Comments for Videos
Yuyan Chen, Yiwen Qian, Songzhou Yan +6
In the era of social media video platforms, popular ``hot-comments'' play a crucial role in attracting user impressions of short-form videos, making them vital for marketing and br…
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…
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…
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…
Dr.Academy: A Benchmark for Evaluating Questioning Capability in Education for Large Language Models
Yuyan Chen, Chenwei Wu, Songzhou Yan +3
Teachers are important to imparting knowledge and guiding learners, and the role of large language models (LLMs) as potential educators is emerging as an important area of study. R…