collaborators

5 papers

cs.LG2026

ChemAmp: Amplified Chemistry Tools via Composable Agents

Zhucong Li, Powei Chang, Jin Xiao +6

Although LLM-based agents are proven to master tool orchestration in scientific fields, particularly chemistry, their single-task performance remains limited by underlying tool con…

cs.AI2025

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs

Jiaxiang Chen, Zhuo Wang, Mingxi Zou +4

Large language models (LLMs) have advanced general-purpose reasoning, showing strong performance across diverse tasks. However, existing methods often rely on implicit exploration,…

cs.IR2025

SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection

Jiale Zhang, Jiaxiang Chen, Zhucong Li +5

Retrieval-Augmented Generation (RAG) enhances language models by incorporating external knowledge at inference time. However, graph-based RAG systems often suffer from structural o…

cs.AI2025

AI2Agent: An End-to-End Framework for Deploying AI Projects as Autonomous Agents

Jiaxiang Chen, Jingwei Shi, Lei Gan +6

As AI technology advances, it is driving innovation across industries, increasing the demand for scalable AI project deployment. However, deployment remains a critical challenge du…

cs.CE2025

ChemHTS: Hierarchical Tool Stacking for Enhancing Chemical Agents

Zhucong Li, Jin Xiao, Bowei Zhang +5

Large Language Models (LLMs) have demonstrated remarkable potential in scientific research, particularly in chemistry-related tasks such as molecular design, reaction prediction, a…