6 papers
Co-RL: Unsupervised Reasoning Emerges from Diverse Cohort in Multi-agent RL
Yunhao Yang, Yuexin Bian, Yunjie Tian +6
Reinforcement learning (RL) has emerged as a powerful approach for improving reasoning in language and vision-language models, yet its strongest successes still depend heavily on g…
Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions
Yijiang Li, Huiqi Zou, Bingyang Wang +1
Multi-modal Large Language Models (MLLMs) have made substantial advances on benchmarks, yet their real-world effectiveness remains uncertain. This gap stems from the fundamental mi…
LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
Wei Luo, Yiting Lu, Xin Li +32
This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and 4D generation settings. The…
Synthetic Users, Real Differences: an Evaluation Framework for User Simulation in Multi-Turn Conversations
Yu Lu Liu, Hyokun Yun, Tanya Roosta +1
There is growing interest in exploring user simulation as an alternative to gathering and scoring real user-chatbot interactions for AI chatbot evaluation. For this purpose, it is…
ByteSized32Refactored: Towards an Extensible Interactive Text Games Corpus for LLM World Modeling and Evaluation
Haonan Wang, Junfeng Sun, Xingdi Yuan +2
Simulating interactive world models remains a core challenge in Large Language Models(LLMs). In this work, we introduce the ByteSized32Refactored, a refactored, modular, and extens…
Can Language Models Serve as Text-Based World Simulators?
Ruoyao Wang, Graham Todd, Ziang Xiao +4
Virtual environments play a key role in benchmarking advances in complex planning and decision-making tasks but are expensive and complicated to build by hand. Can current language…