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New OAR strategy improves LLM agent routing for siloed data

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new routing strategy called Ownership-Aware Routing (OAR) for Large Language Model (LLM) agents that query siloed tables within organizations. Traditional methods like "fan out" (sending queries to all owners simultaneously) or "relay" (querying owners sequentially) are shown to be suboptimal, with accuracy heavily dependent on data ownership rather than query structure. OAR addresses this by first drafting a schema-only SQL query to identify the number of owners whose tables are involved, and then routing the question accordingly before any private row data is accessed. This approach demonstrates comparable or superior accuracy to fixed protocols across various settings, including the PeopleJoin and BIRD datasets. AI

IMPACT This new routing strategy could enhance the efficiency and accuracy of LLM agents interacting with complex, siloed organizational data.

RANK_REASON Academic paper detailing a new method for LLM agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New OAR strategy improves LLM agent routing for siloed data

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Academic paper detailing a new method for LLM agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Zhexi Feng ·

    Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables

    Inside organizations, a question's data often sit with several owners, who query their own tables but never hand them over. An LLM coordinator can fan out, sending the question to every owner at once, or relay, querying owners in turn and reusing earlier rows. We show that neithe…

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