4 papers
Inducing Reasoning Primitives from Agent Traces
Zhihan Lei, Jiarui Yan, Joshua Momo +1
ReAct-style LLM agents often rediscover the same reasoning routines across problems, yet leave those routines trapped in transient scratchpads. We introduce Reasoning Primitive Ind…
Learning to Construct Practical Agentic Systems
Aditya Kumar, Zhihan Lei, Jerry Yan +6
Automated design and optimization of agentic LLM-based systems leads to sophisticated systems that substantially improve result quality over off-the-shelf agentic patterns. However…
GRAG: Graph Retrieval-Augmented Generation
Yuntong Hu, Zhihan Lei, Zheng Zhang +3
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in…
CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs
Yuntong Hu, Zhihan Lei, Zhongjie Dai +4
Research question answering requires accurate retrieval and contextual understanding of scientific literature. However, current Retrieval-Augmented Generation (RAG) methods often s…