2 citations · 6 across the 9 of their papers we have counts for
8 papers · 1 filter
SocialReasonBench: A Video-QA Benchmark for Social Reasoning with Counterfactual Narrative Videos
Zheyu Huang, Zijing Shi, Haozhe Luo +4
Recent advances in Large Multimodal Models (LMMs) have greatly improved video understanding, yet their ability to reason about human-centered social situations remains limited. Exi…
Benchmarking Web Agent Safety under E-commerce Deceptive Interfaces
Zijing Shi, Meng Fang, Ling Chen
As autonomous web agents are increasingly deployed to perform real-world tasks, ensuring their safety has become a critical concern. In this work, we study web agent behavior under…
Vision-Language Reasoning for Geolocalization: A Reinforcement Learning Approach
Biao Wu, Meng Fang, Ling Chen +3
Recent advances in vision-language models have opened up new possibilities for reasoning-driven image geolocalization. However, existing approaches often rely on synthetic reasonin…
Spiral of Silence in Large Language Model Agents
Mingze Zhong, Meng Fang, Zijing Shi +5
The Spiral of Silence (SoS) theory holds that individuals with minority views often refrain from speaking out for fear of social isolation, enabling majority positions to dominate…
Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving
Shunfeng Zheng, Yudi Zhang, Meng Fang +4
Retrieval-augmented generation (RAG) with foundation models has achieved strong performance across diverse tasks, but their capacity for expert-level reasoning-such as solving Olym…
Monte Carlo Planning with Large Language Model for Text-Based Game Agents
Zijing Shi, Meng Fang, Ling Chen
Text-based games provide valuable environments for language-based autonomous agents. However, planning-then-learning paradigms, such as those combining Monte Carlo Tree Search (MCT…
Large Language Models Are Neurosymbolic Reasoners
Meng Fang, Shilong Deng, Yudi Zhang +4
A wide range of real-world applications is characterized by their symbolic nature, necessitating a strong capability for symbolic reasoning. This paper investigates the potential a…
Cooperation on the Fly: Exploring Language Agents for Ad Hoc Teamwork in the Avalon Game
Zijing Shi, Meng Fang, Shunfeng Zheng +3
Multi-agent collaboration with Large Language Models (LLMs) demonstrates proficiency in basic tasks, yet its efficiency in more complex scenarios remains unexplored. In gaming envi…