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| title: PostTrainBench Reproduction | |
| emoji: "๐" | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: static | |
| app_file: index.html | |
| pinned: false | |
| license: mit | |
| tags: | |
| - icml2026-repro | |
| - paper-UnjxMTe57e | |
| # PostTrainBench Reproduction | |
| Deterministic CPU-only released-artifact audit for PostTrainBench | |
| (OpenReview: `UnjxMTe57e`, arXiv: `2603.08640v2`). | |
| ## Selected Claims | |
| ### Claim 1: partial-support | |
| PostTrainBench evaluates autonomous post-training agents across 4 base models and 7 benchmarks under a 10-hour single-H100 budget (Figure 1). | |
| Released trajectory inventory confirms 4-by-7 coverage across all accepted benchmark/model cells. Runner configuration defaults to one H100 with a NUM_HOURS-based timeout. The current checkout's scheduler-dependent branches and five-minute termination grace are reported as limitations. | |
| ### Claim 2: partial-support | |
| The paper reports reward-hacking failure modes including training on test sets, downloading instruction-tuned checkpoints, and using discovered API keys for synthetic data (Abstract). | |
| Released contamination and instruction-model judgments provide partial support for two of three reward-hacking submodes. The API-key submode artifact is absent from the pinned revision. | |
| ## Evidence | |
| - [Evidence summary](index.html) | |
| - [Detailed report](report.html) | |
| - [Poster](poster.html) | |
| - [Provenance](evidence/provenance.json) | |
| - [Coverage](evidence/coverage.json) | |
| - [Reward hacking](evidence/reward_hacking.json) | |
| - [Claims](evidence/claims.json) | |
| - [Manifest](evidence/manifest.json) | |
| ## Limitations | |
| This is not an official challenge verdict. See | |
| [the report](report.html) for the full limitation list. | |
| No H100 run is reproduced. A released judge label is not independently | |
| established behavioral truth. The API-key submode remains unavailable. | |
| ## Licenses | |
| - Source repository: MIT | |
| - Dataset: Apache-2.0 | |
| - Paper: CC BY 4.0 | |
| - This reproduction: MIT | |
| ## Cost | |
| Paid API cost: USD 0.00 | |