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add OASM model from Hadidi et al. 2025#355

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mike-ferguson merged 5 commits intomainfrom
oasm
Feb 12, 2026
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add OASM model from Hadidi et al. 2025#355
mike-ferguson merged 5 commits intomainfrom
oasm

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@mschrimpf
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Cursor-aided implementation based on the paper.

Preliminary results from local run: 0.34 on Pereira2018-linear
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@KartikP KartikP closed this Feb 10, 2026
@KartikP KartikP reopened this Feb 10, 2026
@mike-ferguson
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Retriggering orchestrator

@mike-ferguson
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@mschrimpf Currently scoring is still coming online. I can add a cursor generated test.py file and push, in ~week or so to retrigger/kick off scoring as needed.

…eproducing Figure 1 on Pereira2018 with both OASM sigma sweep and GPT2-XL, including per-subject evaluation.

Replaced with N x N identity matrix with per-block Guassian smoothing (sigma searched over 48 values as per paper).

Add tests

Co-written by Claude Code (Opus 4.6 High effort) and requiring multiple iterations especially during notebook validation.
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KartikP commented Feb 12, 2026

Attempt at reproducing OASM and the results shown in the paper. Used inspiration from #356 and #361 to match evaluation approach (ridge + story-level groups). Used GPT2-XL to validate analysis. Unclear why the differences in GPT2-XL for contiguous

The colored dots/bar are from paper's source data. Stars represent re-implementation.

NOTE: It is probably best not to have all 48 models as public. Will choose sigma0.9 after tests pass on all of them

@mike-ferguson mike-ferguson added the submission_prepared Attached to a PR is metadata and layer mapping is successful. label Feb 12, 2026
@mike-ferguson mike-ferguson merged commit 8f47b56 into main Feb 12, 2026
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@ebrahimfeghhi
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Attempt at reproducing OASM and the results shown in the paper. Used inspiration from #356 and #361 to match evaluation approach (ridge + story-level groups). Used GPT2-XL to validate analysis. Unclear why the differences in GPT2-XL for contiguous

The colored dots/bar are from paper's source data. Stars represent re-implementation.

NOTE: It is probably best not to have all 48 models as public. Will choose sigma0.9 after tests pass on all of them

Thanks for doing this!

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