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Matching papers

A New Role for Relevance: Guiding Corpus Interaction in Agentic Search

87 upvotes · 27 JUL 2026 · Jiangnan Li, Yuqing Li, Mo Yu et al.

This paper develops a new approach to guiding corpus interaction in agentic search, which uses relevance to improve the accuracy and efficiency of search agents in complex question answering and reasoning tasks. Practitioners may care about this research if they want to build more effective search systems that can quickly and reliably retrieve relevant information.

corpus interactionrelevance-aware searchripgrepagentic searchquery-dependent ranking

From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search

64 upvotes · 27 JUL 2026 · Junlin Liu, Jiangwang Chen, Zixin Song et al.

This paper proposes a new method to improve the performance of large language models on knowledge-intensive tasks by distilling knowledge from proprietary models and using reinforcement learning. Practitioners may care about this approach because it can help bridge the gap between proprietary and open-source models, leading to more effective and robust AI systems.

agentic searchknowledge distillationmulti-agent systemsreinforcement learningopen-source models