works on

From the 1 of 12 linked papers with an AI index.

activity
20242026
collaborators

12 papers

cs.AI2026

TopoAgent: A Self-Evolving Topological Agent for Multimodal Scientific Reasoning

Mingze Xu, Yinghui Li, Jiayi Kuang +5

TopoAgent introduces a graph‑based, self‑evolving framework that breaks down multimodal scientific queries into visual atoms and organizes them in a DAG, allowing dynamic refinemen…

cs.AI2026

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…

cs.AI2026

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…

cs.CV2026

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. Nevertheless, their ability to perform precise composit…

cs.SE2026

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…

cs.CL2026

Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models

Junru Lu, Jiarui Qin, Lingfeng Qiao +35

We introduce Youtu-LLM, a lightweight yet powerful language model that harmonizes high computational efficiency with native agentic intelligence. Unlike typical small models that r…