FreshState: A Prospective Benchmark and Resource for Stale Evidence in Web-Augmented LLMs
Abstract
FreshState v2 is an endpoint-validated, age-matched, source-unique benchmark and reusable resource for stale-evidence prediction in retrieval-augmented language models. The released Task 1 evaluation set contains 524 examples (262 stale + 262 fresh): apartment 59/59, software 63/63, and PyPI 140/140. The construction preserves exact within-domain age matching (KS D = 0, p = 1.0; mean age 9.77 days in both classes), enforces within-class source uniqueness, and has zero within-domain source overlap between the stale and fresh classes. Candidate-change seeds are collected through two evidence paths. For the web domains, Craigslist and GitHub candidate events are emitted by prospective daily monitoring. For PyPI, candidate events are reconstructed from structured registry history over a checkpoint window. Released examples in all domains are retained only after domain-appropriate endpoint validation. Software final answer-bearing values are reconstructed from publicly visible GitHub Releases API history under an API-canonical stable-tag definition: canonical_stable_tag(releases, D) is the latest non-draft, non-prerelease release with published_at <= D 23:59:59 UTC. PyPI answer-bearing values are defined as the latest PEP 440-parseable non-prerelease, non-development release recorded in PyPI registry metadata at the checkpoint date, retaining releases marked as yanked. The bundled PyPI provenance snapshot supports offline verification of all retained PyPI examples; a…
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