REVE: results on public EEG datasets

Foundation model

REVE: results on public EEG datasets

REVE is a pretrained EEG encoder released in Small, Base and Large sizes, all trained on one corpus that its paper's appendix lists: public collections from TUH, PhysioNet, OpenNeuro and MOABB among others, with the recordings of the authors' own downstream tasks removed. BCI Report ran the Base and Large checkpoints frozen, with the published ridge head; their input removes each segment's per-channel mean, a deviation declared before scoring. The weights are under the REVE Responsible Use License, accepted for this site on 4 October 2026.

Measured on: ds003810; EEGMAT; BETA; ds006593; TMNRED / ds005383; EESM19 scalp subset; ds005342 · Protocols: Motor imagery & rest; Arithmetic & rest; SSVEP · 8 channels; SSVEP · 4 channels; P300 target ERP; Semantic target ERP; Sleep staging; Idle & command

Also known as REVE Base · REVE Large · brain-bzh/reve-base · brain-bzh/reve-large

Reference REVE, arXiv:2510.21585 ↗

Directory status: Evaluated · Official code ↗ · Description sources arxiv.org · huggingface.co · huggingface.co · huggingface.co

Published results

Grouped by dataset. Compare figures within a group only: across groups the task, cohort, chance level and electrode layout all change.

ds003810 · v9 foundation encoders, frozen · motor imagery & rest

Read with its protocol: Core-matrix protocol: Motor imagery & rest · Chance level 50.0% · foundation-models-mi-rest.csv

REVE Base

66.2% (61.8%–70.6%)

REVE Large

70.2% (64.0%–76.1%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	66.2%61.8%–70.6%	10
REVE Large	Frozen encoder + ridge head	Balanced accuracy	70.2%64.0%–76.1%	10

Weights terms: REVE under the REVE Responsible Use License v1.0 (model versions: REVE Base @ dc2a075c · REVE Large @ 317531c7). No model’s authors endorse these results. Every weights licence and its terms →

EEGMAT · v9 foundation encoders, frozen · arithmetic & rest

Read with its protocol: Core-matrix protocol: Arithmetic & rest · Chance level 50.0% · foundation-models-arithmetic-rest.csv

REVE Base

68.8% (64.1%–73.2%)

REVE Large

69.0% (63.3%–74.7%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	68.8%64.1%–73.2%	36
REVE Large	Frozen encoder + ridge head	Balanced accuracy	69.0%63.3%–74.7%	36

EEGMAT · Model adaptation, v9 · new people, same task, one fixed recipe (not a ranking)

Read with its protocol: Core-matrix protocol: Arithmetic & rest · Chance level 50.0% · foundation-models-update.json

REVE Base · Frozen encoder + trained head

64.0% (60.4%–67.7%)

REVE Base · LoRA rank 4 + head

66.3% (61.9%–70.7%)

REVE Large · Frozen encoder + trained head

65.6% (61.1%–70.1%)

REVE Large · LoRA rank 4 + head

69.2% (63.4%–74.9%)

Balanced accuracy, 4 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + trained head	Balanced accuracy	64.0%60.4%–67.7%1,026 trainable parameters.	36
REVE Base	LoRA rank 4 + head	Balanced accuracy	66.3%61.9%–70.7%181,250 trainable parameters.	36
REVE Base	LoRA minus frozen + head, same people and folds	Paired difference	+2.3 pp+0.1 pp–+4.6 pp21 people improved, 13 got worse, 2 unchanged. The interval excludes zero.	36
REVE Large	Frozen encoder + trained head	Balanced accuracy	65.6%61.1%–70.1%2,434 trainable parameters.	36
REVE Large	LoRA rank 4 + head	Balanced accuracy	69.2%63.4%–74.9%430,466 trainable parameters.	36
REVE Large	LoRA minus frozen + head, same people and folds	Paired difference	+3.6 pp+0.5 pp–+6.8 pp21 people improved, 13 got worse, 2 unchanged. The interval excludes zero.	36

BETA · v9 foundation encoders, frozen · SSVEP, 8 channels

Read with its protocol: Core-matrix protocol: SSVEP · 8 channels · Chance level 2.5% · foundation-models-beta-8ch.csv

REVE Base

37.5% (33.3%–41.9%)

REVE Large

52.7% (47.7%–57.8%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	37.5%33.3%–41.9%	70
REVE Large	Frozen encoder + ridge head	Balanced accuracy	52.7%47.7%–57.8%	70

BETA · v9 foundation encoders, frozen · SSVEP, 4 channels

Read with its protocol: Core-matrix protocol: SSVEP · 4 channels · Chance level 2.5% · foundation-models-beta-4ch.csv

REVE Base

25.5% (22.4%–28.8%)

REVE Large

46.4% (41.7%–51.2%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	25.5%22.4%–28.8%	70
REVE Large	Frozen encoder + ridge head	Balanced accuracy	46.4%41.7%–51.2%	70

ds006593 · v9 foundation encoders, frozen · P300 target ERP

Read with its protocol: Core-matrix protocol: P300 target ERP · Chance level 50.0% · foundation-models-p300-target.csv

REVE Base

50.5% (48.5%–52.3%)

REVE Large

54.6% (52.7%–56.5%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	50.5%48.5%–52.3%	21
REVE Large	Frozen encoder + ridge head	Balanced accuracy	54.6%52.7%–56.5%	21

TMNRED / ds005383 · v9 foundation encoders, frozen · semantic target ERP

Read with its protocol: Core-matrix protocol: Semantic target ERP · Chance level 50.0% · foundation-models-semantic-target.csv

REVE Base

53.7% (51.8%–55.4%)

REVE Large

59.7% (57.5%–61.8%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	53.7%51.8%–55.4%	30
REVE Large	Frozen encoder + ridge head	Balanced accuracy	59.7%57.5%–61.8%	30

EESM19 scalp subset · v9 foundation encoders, frozen · sleep staging

Read with its protocol: Core-matrix protocol: Sleep staging · Chance level 20.0% · foundation-models-sleep-scalp.csv

REVE Base

74.6% (72.9%–76.4%)

REVE Large

76.6% (75.2%–78.0%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + ridge head	Balanced accuracy	74.6%72.9%–76.4%	20
REVE Large	Frozen encoder + ridge head	Balanced accuracy	76.6%75.2%–78.0%	20

ds005342 · v9 foundation encoders, frozen · idle & command

Read with its protocol: Core-matrix protocol: Idle & command · foundation-models-idle.csv

Method	Condition	Metric	Value	People
REVE Base	Frozen encoder + linear head	Commands detected ≤3 s	12 / 600 of 4 people always abstained.	4
REVE Base	Frozen encoder + linear head	Idle false activations	1 / 60	4
REVE Large	Frozen encoder + linear head	Commands detected ≤3 s	6 / 602 of 4 people always abstained.	4
REVE Large	Frozen encoder + linear head	Idle false activations	1 / 60	4

All methods → · All datasets →

Checkpoints, inputs and terms

What was run, as the v9 release records it: each checkpoint’s revision and SHA-256, its encoder parameters, the footnote its rows carry and its weights licence. No weights, adapted weights or LoRA deltas were kept or shared, and no endorsement by the model’s authors is implied.

REVE Base

Panel: A row beside the core matrix on every protocol page
Encoder parameters: 69.19M
Revision: brain-bzh/reve-base @ dc2a075c
Checkpoint SHA-256: 8ecc650619598748286c2457f81f5c6bd12e8bb59db44f7b02af1955c44de8fe
Paper: paper ↗
Weights licence: REVE Responsible Use License v1.0 (owner-approved 2026-10-04)
Licence note: REVE Responsible Use License v1.0: aggregate scientific results only; no re-identification, model inversion, membership inference or non-consensual profiling; cite the REVE paper and name the model version; no adapted weights shared.
Rights review: Accepted by the owner on 2026-10-04. Aggregate scientific results only; no re-identification, model inversion, membership inference or non-consensual profiling; the REVE paper is cited and the model version named; no adapted weights are shared.
Row footnote: Input removes the per-segment per-channel mean before the published /100 scaling (declared before scoring); a no-mean-removal sensitivity run scores P300 0.71 percentage points higher and sleep 1.40 lower.
Notes: REVE input removes the per-segment per-channel mean (declared before scoring; the published LaBraM/CBraMod rows did not); a no-mean-removal sensitivity run is stated in the row footnote.
EEGMAT adaptation: Run: a head trained on the frozen encoder against LoRA rank 4, three seeds.

REVE Large

Panel: A row beside the core matrix on every protocol page
Encoder parameters: 389.98M
Revision: brain-bzh/reve-large @ 317531c7
Checkpoint SHA-256: f519428404aab27f7db816722c7fb8c73d08daf10986c9c21b0066be9e93bb31
Paper: paper ↗
Weights licence: REVE Responsible Use License v1.0 (owner-approved 2026-10-04)
Licence note: REVE Responsible Use License v1.0 (as REVE Base).
Rights review: Accepted by the owner on 2026-10-04. Aggregate scientific results only; no re-identification, model inversion, membership inference or non-consensual profiling; the REVE paper is cited and the model version named; no adapted weights are shared.
Row footnote: Input removes the per-segment per-channel mean (declared before scoring); the no-mean-removal sensitivity run scores P300 2.06 percentage points lower and sleep 0.93 lower.
Notes: REVE input removes the per-segment per-channel mean (declared before scoring); a no-mean-removal sensitivity run is stated in the row footnote.
EEGMAT adaptation: Run: a head trained on the frozen encoder against LoRA rank 4, three seeds.

Pretraining exposure, by dataset

Whether each core dataset is in the model authors’ published pretraining list, checked on 2026-10-04 and linked to the source. A dataset absent from the list is not proof that its recordings were never seen; recording-level audits were not done.

REVE Base · REVE Large

Dataset	Protocols	Statement	Source
ds003810 Motor Imagery vs Rest (low-cost EEG; Peterson et al.)	Motor imagery & rest	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗
EEGMAT (PhysioNet EEG During Mental Arithmetic Tasks; Zyma et al. 2019)	Arithmetic & rest	not in the authors' published pretraining list (checked 2026-10-04)	source ↗
ds006593 cBCI Matrix Multimodal Dataset (Celik et al.)	P300 target ERP	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗
ds005383 TMNRED (Bai et al. 2025, Sci. Data 12:701)	Semantic target ERP	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗
EESM19 Ear-EEG Sleep Monitoring 2019 (OpenNeuro ds005185; Mikkelsen et al.)	Sleep staging	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗
BETA 40-target SSVEP (Liu et al. 2020, Front. Neurosci. 14:627)	SSVEP · 8 channels · SSVEP · 4 channels	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗ · source ↗
ds005342 EEG offline/online MI for standing and sitting (Triana-Guzman et al.)	Idle & command	not in the authors' published pretraining list (checked 2026-10-04)	source ↗ · source ↗ · source ↗

Note on the check: REVE's Table 7 counts 27 MOABB datasets but names 25 (26 with the open-subset card); the unnamed slot cannot be BETA or ds005342 because MOABB added those loaders only in March 2026.

Cite this page

BCI Report (2026). REVE: results on public EEG datasets. https://bci.report/methods/reve/

Figures from release foundation-models-update-20261004 (2026-10-04). Cite the upstream datasets as well: each dataset’s page gives its credit.

Every release is archived on Zenodo: doi:10.5281/zenodo.23123296. BibTeX for the site and its releases → · CITATION.cff ↗