Studying Without a Syllabus: Task-Agnostic Environment Preprocessing
Agents can prepare useful tools for unknown tasks, but more study time is not a guarantee.
The paper formalizes “task-agnostic environment preprocessing,” where an agent explores a new environment under a budget and leaves artifacts for a frozen solver. Across six benchmarks, a meta-agent variant led Avg@3 reward on five, while fixed corpus processing won on the largest corpus benchmark. The authors also found that larger study budgets did not reliably improve downstream reward. The main gain was efficiency: prepared artifacts reduced the test-time sampling needed to reach a given score. HF Daily Papers' note
The paper formalizes “task-agnostic environment preprocessing,” where an agent explores a new environment under a budget and leaves artifacts for a frozen solver. Across six benchmarks, a meta-agent variant led Avg@3 reward on five, while fixed corpus processing won on the largest corpus benchmark. The authors also found that larger study budgets did not reliably improve downstream reward. The main gain was efficiency: prepared artifacts reduced the test-time sampling needed to reach a given score. HF Daily Papers' note
score 5