{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KKKYVVGNWKNLPHSRXIAWN6L7W3","short_pith_number":"pith:KKKYVVGN","canonical_record":{"source":{"id":"2311.03764","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-07T07:07:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"902c0a2c8aa87625d5caefde23a36e79cc5275b87a90b78caa72e7e5e4ffe19a","abstract_canon_sha256":"68b4d621a8dad38b51b6cb52b1d5f1aeda368689e41b2f7c3606baede5d81b66"},"schema_version":"1.0"},"canonical_sha256":"52958ad4cdb29ab79e51ba0166f97fb6d94bc5ef8148409c20b0991e3851283c","source":{"kind":"arxiv","id":"2311.03764","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.03764","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"2311.03764v4","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.03764","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"KKKYVVGNWKNL","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_16","alias_value":"KKKYVVGNWKNLPHSR","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_8","alias_value":"KKKYVVGN","created_at":"2026-07-05T07:51:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KKKYVVGNWKNLPHSRXIAWN6L7W3","target":"record","payload":{"canonical_record":{"source":{"id":"2311.03764","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-07T07:07:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"902c0a2c8aa87625d5caefde23a36e79cc5275b87a90b78caa72e7e5e4ffe19a","abstract_canon_sha256":"68b4d621a8dad38b51b6cb52b1d5f1aeda368689e41b2f7c3606baede5d81b66"},"schema_version":"1.0"},"canonical_sha256":"52958ad4cdb29ab79e51ba0166f97fb6d94bc5ef8148409c20b0991e3851283c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:51:10.616383Z","signature_b64":"1uHwLszy4shRPgLcI2zSwGsrZ+V9RBz68wNtagqQt+9a9XNor8JkTQdnE8JLakRkyUu2z2eXpISJ2k99iEFUBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"52958ad4cdb29ab79e51ba0166f97fb6d94bc5ef8148409c20b0991e3851283c","last_reissued_at":"2026-07-05T07:51:10.615856Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:51:10.615856Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.03764","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RIszBr3NPsvypG9NW3XiiIpjNe5XHBB3L64DXIzgz+gMq+nc17qIIaHs6mpvLEGN4jeZsqdaB+Vlb5PlMsV9Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T02:44:48.907717Z"},"content_sha256":"1c12bc32cba69c215e8e1a0dd0cabe9265977186aac60295d620aeac96c1bf83","schema_version":"1.0","event_id":"sha256:1c12bc32cba69c215e8e1a0dd0cabe9265977186aac60295d620aeac96c1bf83"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KKKYVVGNWKNLPHSRXIAWN6L7W3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neuro-GPT: Towards A Foundation Model for EEG","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.LG","authors_text":"Anand A. Joshi, Karim Jerbi, Philipp Th\\\"olke, Richard M. Leahy, Takfarinas Medani, Wenhui Cui, Woojae Jeong","submitted_at":"2023-11-07T07:07:18Z","abstract_excerpt":"To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-Computer Interface (BCI) tasks, and to harness the power of large publicly available data sets, we propose Neuro-GPT, a foundation model consisting of an EEG encoder and a GPT model. The foundation model is pre-trained on a large-scale data set using a self-supervised task that learns how to reconstruct masked EEG segments. We then fine-tune the model on a Motor Imagery Classification task to validate its performance in a low-data regime (9 subjects). Our experiments demonstrate that applying a foundation m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.03764","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.03764/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y3T91PSl5cSuSIadcBvq1hcRR/oNnLWhVhjVJpRtp9vRb0D5Po2YvNFmg1iWuNddG89DsX+43En+WdlmjP2qCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T02:44:48.908071Z"},"content_sha256":"c6eb3868c5cf84145ae3a6bc62f0cd785d3397e286e57487de0e249143b596ad","schema_version":"1.0","event_id":"sha256:c6eb3868c5cf84145ae3a6bc62f0cd785d3397e286e57487de0e249143b596ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/bundle.json","state_url":"https://pith.science/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-01T02:44:48Z","links":{"resolver":"https://pith.science/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3","bundle":"https://pith.science/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/bundle.json","state":"https://pith.science/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KKKYVVGNWKNLPHSRXIAWN6L7W3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KKKYVVGNWKNLPHSRXIAWN6L7W3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"68b4d621a8dad38b51b6cb52b1d5f1aeda368689e41b2f7c3606baede5d81b66","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-07T07:07:18Z","title_canon_sha256":"902c0a2c8aa87625d5caefde23a36e79cc5275b87a90b78caa72e7e5e4ffe19a"},"schema_version":"1.0","source":{"id":"2311.03764","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.03764","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"2311.03764v4","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.03764","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"KKKYVVGNWKNL","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_16","alias_value":"KKKYVVGNWKNLPHSR","created_at":"2026-07-05T07:51:10Z"},{"alias_kind":"pith_short_8","alias_value":"KKKYVVGN","created_at":"2026-07-05T07:51:10Z"}],"graph_snapshots":[{"event_id":"sha256:c6eb3868c5cf84145ae3a6bc62f0cd785d3397e286e57487de0e249143b596ad","target":"graph","created_at":"2026-07-05T07:51:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2311.03764/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-Computer Interface (BCI) tasks, and to harness the power of large publicly available data sets, we propose Neuro-GPT, a foundation model consisting of an EEG encoder and a GPT model. The foundation model is pre-trained on a large-scale data set using a self-supervised task that learns how to reconstruct masked EEG segments. We then fine-tune the model on a Motor Imagery Classification task to validate its performance in a low-data regime (9 subjects). Our experiments demonstrate that applying a foundation m","authors_text":"Anand A. Joshi, Karim Jerbi, Philipp Th\\\"olke, Richard M. Leahy, Takfarinas Medani, Wenhui Cui, Woojae Jeong","cross_cats":["eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-07T07:07:18Z","title":"Neuro-GPT: Towards A Foundation Model for EEG"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.03764","kind":"arxiv","version":4},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1c12bc32cba69c215e8e1a0dd0cabe9265977186aac60295d620aeac96c1bf83","target":"record","created_at":"2026-07-05T07:51:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"68b4d621a8dad38b51b6cb52b1d5f1aeda368689e41b2f7c3606baede5d81b66","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-07T07:07:18Z","title_canon_sha256":"902c0a2c8aa87625d5caefde23a36e79cc5275b87a90b78caa72e7e5e4ffe19a"},"schema_version":"1.0","source":{"id":"2311.03764","kind":"arxiv","version":4}},"canonical_sha256":"52958ad4cdb29ab79e51ba0166f97fb6d94bc5ef8148409c20b0991e3851283c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"52958ad4cdb29ab79e51ba0166f97fb6d94bc5ef8148409c20b0991e3851283c","first_computed_at":"2026-07-05T07:51:10.615856Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:51:10.615856Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1uHwLszy4shRPgLcI2zSwGsrZ+V9RBz68wNtagqQt+9a9XNor8JkTQdnE8JLakRkyUu2z2eXpISJ2k99iEFUBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:51:10.616383Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.03764","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c12bc32cba69c215e8e1a0dd0cabe9265977186aac60295d620aeac96c1bf83","sha256:c6eb3868c5cf84145ae3a6bc62f0cd785d3397e286e57487de0e249143b596ad"],"state_sha256":"c95b648b27000387ce1a4e9d10a1b539f8e39787c27e33e64c2aebb6b68789fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XaTV3ckaqPiJgSHO8m3mViYBl0RDIn3m8ZplUnP2KMr78+3YRWLJYK/56fuGuBKwZHbLiknF40TbYb8EL8JLDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T02:44:48.910387Z","bundle_sha256":"945ea830fd4e010d77bd6244438a31e695a1dc6233d563a3c8283a4d57ecf0af"}}