8 papers
Deep Thought Alignment: Trajectory-Level Latent Distillation for Video Reasoning
Ao Shen, Yongheng Zhang, Yinghui Li +3
Large Multimodal Models (LMMs) for video reasoning have long been hindered by the high computational cost of processing vast amounts of visual information. This dilemma motivates t…
From Atomic to Agentic: Towards Interpretable Evaluation of LLMs' Agentic Mathematical Capabilities
Jiayi Kuang, Yinghui Li, Yunze Song +11
Large Language Models (LLMs) are evolving from performing end-to-end mathematical reasoning to integrating agentic intelligence. However, most existing math benchmarks evaluate onl…
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI
Yongheng Zhang, Ziang Liu, Jiaxuan Zhu +17
Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reasoning, action, memory, and self-im…
Thinking in Video: Can Video Generators Really Reason About the Real World?
Yongheng Zhang, Guang Yang, Ruihan Hou +12
Recent advances in world models and video generation have given rise to an emerging reasoning paradigm that leverages video generative models to simulate, predict, and reason about…
TopoAgent: A Self-Evolving Topological Agent for Multimodal Scientific Reasoning
Mingze Xu, Yinghui Li, Jiayi Kuang +5
While Multimodal Large Language Models (MLLMs) excel in general tasks, rigorous scientific reasoning remains challenging due to the limitations of monolithic, linear planning. Such…
Latent Visual Cache for Video Reasoning
Yongheng Zhang, Zhipeng Xu, Hao Wu +4
Video reasoning requires Large Multimodal Models (LMMs) to remain grounded in dense evidence, yet existing systems largely adopt "read-once, generate-many" paradigm, in which visua…
EvoConfig: Self-Evolving Multi-Agent Systems for Efficient Autonomous Environment Configuration
Xinshuai Guo, Jiayi Kuang, Linyue Pan +6
A reliable executable environment is the foundation for ensuring that large language models solve software engineering tasks. Due to the complex and tedious construction process, l…
TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning
Daixian Liu, Jiayi Kuang, Yinghui Li +8
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compositional spatial reasoning under geome…