RESEARCHMonitorWATCHLIST
Benchmarking and Error Analysis of Deep Search and Deep Research LLM Agents
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
An arXiv research paper introduces benchmarking for deep search LLM agents, focusing on error analysis across multi-step execution traces.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 22 October 2026
- Collected by OneBench
- 23 Oct 2026, 03:02 UK
Stored source excerpt
arXiv:2610.29346v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into autonomous Deep Search and Deep Research Agents capable of executing long-horizon, multi-step tasks,…
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