The Scheduler Is a Hidden Retriever: How Asynchrony Shapes Evidence Acquisition in Search Agents

Key points

• Language-model agents increasingly solve complex tasks through parallel reasoning and asynchronous information gathering.1
• Controlled replay across two model families and three benchmarks shows that delivery timing redirects search decisions made before all results arrive, despite identical initial evidence.1
• An acquisition-regret bound with a matching construction shows that invariance at a fixed early arrival count can limit the use of evidence already received.1
• For a fixed plan and stable conditional response law, we prove joint invariance of decisions, acquisitions, and answers.1

Sources (1)

• [1]The Scheduler Is a Hidden Retriever: How Asynchrony Shapes Evidence Acquisition in Search Agents
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 12:55 PM

  We introduce Confluent Evidence Acquisition (CEA), which instead releases local reasoning when each subquestion's evidence is complete and allocates shared search independently of completion order.

  Language-model agents increasingly solve complex tasks through parallel reasoning and asynchronous information gathering.

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