Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document Collections research paper by Snowflake, 2026

Snowflake · Mar 12, 2026 · Agents and evaluation · 1 citations · 66 upvotes

On 2,250 questions over 800 PDFs, the best agents match human accuracy but lean on brute-force search rather than planning.

Summarised by hand from the abstract.

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Jun 3, 2026	Agents' Last ExamOver 1,000 real, checkable professional tasks written with 250+ industry experts; the hardest tier is far from solved.UC Berkeley · Jun 2026UC Berkeley	UC Berkeley	15
Sep 21, 2026	RRSI: Regularized Recursive Self-Improvement of Agent HarnessesRRSI keeps self-improving agent harnesses from memorising their training tasks, so gains carry over to new benchmarks.Google · Sep 2026Google	Google	0

About this paper

Authors: Łukasz Borchmann, Jordy Van Landeghem, Michał Turski and 12 more
arXiv: 2603.12180 · PDF
Venue: arXiv.org
Citations: 1, 0 influential · Semantic Scholar
Upvotes: 66 · Hugging Face
Code: github.com/OxRML/MADQA
Lab: Snowflake · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

Date	What changed
Sep 24, 2026	New paperAdded to the listSep 24, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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