most citedEgoSocialArena: Benchmarking the Social Intelligence of Large Language Models from a First-person Perspective

1 citations · 3 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CL2025

Active Confusion Expression in Large Language Models: Leveraging World Models toward Better Social Reasoning

Jialu Du, Guiyang Hou, Yihui Fu +4

While large language models (LLMs) excel in mathematical and code reasoning, we observe they struggle with social reasoning tasks, exhibiting cognitive confusion, logical inconsist…

cs.CL2025★ 1 cited

Cooper: Co-Optimizing Policy and Reward Models in Reinforcement Learning for Large Language Models

Haitao Hong, Yuchen Yan, Xingyu Wu +5

Large language models (LLMs) have demonstrated remarkable performance in reasoning tasks, where reinforcement learning (RL) serves as a key algorithm for enhancing their reasoning…

cs.CV2025

SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation

Siqi Chen, Xinyu Dong, Haolei Xu +10

Large Language Models (LLMs) and Multimodal LLMs have shown promising capabilities for SVG processing, yet existing benchmarks suffer from limited real-world coverage, lack of comp…

cs.CL2025

TimeHC-RL: Temporal-aware Hierarchical Cognitive Reinforcement Learning for Enhancing LLMs' Social Intelligence

Guiyang Hou, Xing Gao, Yuchuan Wu +8

Recently, Large Language Models (LLMs) have made significant progress in IQ-related domains that require careful thinking, such as mathematics and coding. However, enhancing LLMs'…

cs.CV2025

ViewSpatial-Bench: Evaluating Multi-perspective Spatial Localization in Vision-Language Models

Dingming Li, Hongxing Li, Zixuan Wang +9

Vision-language models (VLMs) have demonstrated remarkable capabilities in understanding and reasoning about visual content, but significant challenges persist in tasks requiring c…

cs.HC2025★ 1 cited

A Survey on (M)LLM-Based GUI Agents

Fei Tang, Haolei Xu, Hang Zhang +12

Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-drive…

cs.AI2025

Think Twice, Click Once: Enhancing GUI Grounding via Fast and Slow Systems

Fei Tang, Yongliang Shen, Hang Zhang +7

Humans can flexibly switch between different modes of thinking based on task complexity: from rapid intuitive judgments to in-depth analytical understanding. However, current Graph…

cs.CL2025

Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks

Wenqi Zhang, Mengna Wang, Gangao Liu +10

Recent advances in deep thinking models have demonstrated remarkable reasoning capabilities on mathematical and coding tasks. However, their effectiveness in embodied domains which…

cs.IR2024

GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation

Fei Tang, Yongliang Shen, Hang Zhang +6

Large language model-based explainable recommendation (LLM-based ER) systems show promise in generating human-like explanations for recommendations. However, they face challenges i…

cs.CL2024★ 1 cited

EgoSocialArena: Benchmarking the Social Intelligence of Large Language Models from a First-person Perspective

Guiyang Hou, Wenqi Zhang, Yongliang Shen +3

Social intelligence is built upon three foundational pillars: cognitive intelligence, situational intelligence, and behavioral intelligence. As large language models (LLMs) become…

cs.CV2024

Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model

Wenqi Zhang, Zhenglin Cheng, Yuanyu He +8

Although most current large multimodal models (LMMs) can already understand photos of natural scenes and portraits, their understanding of abstract images, e.g., charts, maps, or l…

cs.CL2024

TimeToM: Temporal Space is the Key to Unlocking the Door of Large Language Models' Theory-of-Mind

Guiyang Hou, Wenqi Zhang, Yongliang Shen +2

Theory of Mind (ToM)-the cognitive ability to reason about mental states of ourselves and others, is the foundation of social interaction. Although ToM comes naturally to humans, i…

cs.AI2024

Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization

Wenqi Zhang, Ke Tang, Hai Wu +7

Large Language Models (LLMs) exhibit robust problem-solving capabilities for diverse tasks. However, most LLM-based agents are designed as specific task solvers with sophisticated…