Add QMSD-Encoder-v1.1 submission#121
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Sounds good @d0ng231! Just as a quick note, you can update or add new methods to an existing PR by including them in a new folder. It's also fine to do as separate PRs -- up to you. Thanks for submitting to RAID! |
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Eval run succeeded! Link to run: link Here are the results of the submission(s): QMSD-Encoder-v1.1Release date: 2026-04-26 I've committed detailed results of this detector's performance on the test set to this PR. On the RAID dataset as a whole (aggregated across all generation models, domains, decoding strategies, repetition penalties, and adversarial attacks), it achieved an AUROC of 99.68 and a TPR of 99.52% at FPR=5% and 97.82% at FPR=1%. If all looks well, a maintainer will come by soon to merge this PR and your entry/entries will appear on the leaderboard. If you need to make any changes, feel free to push new commits to this PR. Thanks for submitting to RAID! |
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Eval run succeeded! Link to run: link Here are the results of the submission(s): QMSD-Encoder-v1.2Release date: 2026-04-27 I've committed detailed results of this detector's performance on the test set to this PR. On the RAID dataset as a whole (aggregated across all generation models, domains, decoding strategies, repetition penalties, and adversarial attacks), it achieved an AUROC of 99.90 and a TPR of 99.74% at FPR=5% and 98.53% at FPR=1%. QMSD-Encoder-v1.2-miniRelease date: 2026-04-27 I've committed detailed results of this detector's performance on the test set to this PR. On the RAID dataset as a whole (aggregated across all generation models, domains, decoding strategies, repetition penalties, and adversarial attacks), it achieved an AUROC of 99.30 and a TPR of 99.46% at FPR=5% and 86.78% at FPR=1%. If all looks well, a maintainer will come by soon to merge this PR and your entry/entries will appear on the leaderboard. If you need to make any changes, feel free to push new commits to this PR. Thanks for submitting to RAID! |
Submitting QMSD-Encoder-v1.1 to the RAID leaderboard.
Thanks to the maintainers for the quick response on the previous PR.
This is an interim version; we'll release more complete results + the model alongside an upcoming paper, and decide then which version to merge into the main leaderboard.