Tao Yin
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DeepGuard introduces a novel multi-layer semantic aggregation framework to enhance secure code generation by collecting vulnerability cues from multiple upper layers of LLMs, significantly improving security while maintaining functional correctness.
The paper introduces PlanRAG, a framework for Retrieval-Augmented Generation (RAG) that models exploratory reasoning problems as logical query trees, addressing representation and optimization gaps between structured SQL and unstructured natural language.
Papers
When RAG Meets Query Planning: Logical Query Trees for Resolving Exploratory Reasoning Problems
Ganlin Xu, Linghao Zhang, Zhitao Yin, Hongda Xi +6 more
The paper introduces PlanRAG, a framework for Retrieval-Augmented Generation (RAG) that models exploratory reasoning problems as logical query trees, addressing representation and optimization gaps be…