Papers by Yueming Jin

2 papers
Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Tools (2025.acl-long)

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Challenge: Existing reasoning methods excel in structured domains like math and code, but they are not all effective in knowledge-intensive tasks.
Approach: They introduce a framework that enhances large language model reasoning by integrating external tool-using agents.
Outcome: The proposed framework achieves state-of-the-art among public models and delivers comparable performance to OpenAI Deep Research.
Medical Graph RAG: Evidence-based Medical Large Language Model via Graph Retrieval-Augmented Generation (2025.acl-long)

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Challenge: GraphRAG framework is designed to enhance LLMs in generating evidence-based medical responses.
Approach: They propose a graph-based Retrieval-augmented generation framework to enhance LLMs in generating evidence-based medical responses.
Outcome: The proposed framework outperforms state-of-the-art models on 9 medical Q&A benchmarks, 2 health fact-checking datasets, and a long-form generation test set.

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