2 citations · 5 across the 16 of their papers we have counts for
8 papers · 1 filter
INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning
Shuai Wang, Jiayi Kuang, Yinghui Li +4
Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness, raising the question wheth…
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…
PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution
Yang Liu, Weixing Chen, Xinshuai Song +8
Vision-language-action models, world models, and agentic planners each advance physical intelligence, yet their composition lacks a common execution abstraction, shared state, sema…
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…
Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding
Yinghui Li, Jiayi Kuang, Peng Xing +11
Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains unclear. We present a multi-domain benc…
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…