Brief
Agent can study an unfamiliar environment before test time, paper finds
A new arXiv paper formalizes task-agnostic environment preprocessing: an agent explores an unfamiliar environment under a budget, before test time, and builds reusable artifacts for a frozen solver.
An LLM agent can inspect available corpora and tools in a new environment and build reusable resources such as indices, scripts or procedural guidance. The paper asks whether it can do that without a syllabus — before test time and without knowing the downstream task distribution — and choose how to prepare the environment.
Across six heterogeneous benchmarks, a meta-agent variant achieved the highest Avg@3 reward on five, while fixed corpus processing stayed best on the largest corpus benchmark. Larger study budgets did not reliably improve downstream reward.
The practical result: studied artifacts reduce the test-time sampling needed to reach a given score, shifting computation from repeated test-time attempts to a pre-task study phase.
Source details and supporting facts
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Stated by arXiv
- The paper formalizes task-agnostic environment preprocessing, in which a studying system explores an environment under a budget and produces artifacts for a frozen solver.
- A meta-agent variant achieves the highest Avg@3 reward on five benchmarks.
- Fixed corpus processing remains best on the largest corpus benchmark.
- Larger study budgets do not reliably improve downstream reward.
- Studied artifacts reduce the test-time sampling needed to reach a given score.
Sources
- arXivText stored 13 September 2026
How this story was checked. Written from the 1 page listed above, stored 13 September 2026; claims checked against that stored text on 14 September 2026.
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