{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:4EVMLTBVP7Q3NHDPBJ7FP27OBB","short_pith_number":"pith:4EVMLTBV","canonical_record":{"source":{"id":"2211.02625","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-27T21:43:35Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f0ed2b4c625beb6aae07312e6309bb1aeaa7243aa822aded1b583be81ab09964","abstract_canon_sha256":"707a4f1ef6189e7b985aeff08077c0492cee22990d8d8dfeb2342a19709f85a1"},"schema_version":"1.0"},"canonical_sha256":"e12ac5cc357fe1b69c6f0a7e57ebee087be0ea6698d84085d3605df365865f3a","source":{"kind":"arxiv","id":"2211.02625","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.02625","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"arxiv_version","alias_value":"2211.02625v1","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.02625","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_12","alias_value":"4EVMLTBVP7Q3","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_16","alias_value":"4EVMLTBVP7Q3NHDP","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_8","alias_value":"4EVMLTBV","created_at":"2026-07-05T05:13:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:4EVMLTBVP7Q3NHDPBJ7FP27OBB","target":"record","payload":{"canonical_record":{"source":{"id":"2211.02625","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-27T21:43:35Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f0ed2b4c625beb6aae07312e6309bb1aeaa7243aa822aded1b583be81ab09964","abstract_canon_sha256":"707a4f1ef6189e7b985aeff08077c0492cee22990d8d8dfeb2342a19709f85a1"},"schema_version":"1.0"},"canonical_sha256":"e12ac5cc357fe1b69c6f0a7e57ebee087be0ea6698d84085d3605df365865f3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:13:17.414352Z","signature_b64":"4FazYqLbZcNBn1aLJYtUYI1yZxBQpmQ7idt+xpUMLANNGEH0iI1tciUI+mBlfcB3cMOhPIXLi6dG6JUu+KGCDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e12ac5cc357fe1b69c6f0a7e57ebee087be0ea6698d84085d3605df365865f3a","last_reissued_at":"2026-07-05T05:13:17.413931Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:13:17.413931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.02625","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:13:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m8CjHKBrn6B4XjFCY3r3BFOQmBSCJn7FZtVuQ4YlVFDl/bjOGum0vioJa3PB4hKBMvzMJBJpiUqzMUKFdN3cDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:13:36.881609Z"},"content_sha256":"06007b25cf42491e15dd1297e38ae16256c2a8b76e590bc0aee6b93a07b7b47b","schema_version":"1.0","event_id":"sha256:06007b25cf42491e15dd1297e38ae16256c2a8b76e590bc0aee6b93a07b7b47b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:4EVMLTBVP7Q3NHDPBJ7FP27OBB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MAEEG: Masked Auto-encoder for EEG Representation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Christopher M. Sandino, Hanlin Goh, Hsiang-Yun Sherry Chien, Joseph Y. Cheng","submitted_at":"2022-10-27T21:43:35Z","abstract_excerpt":"Decoding information from bio-signals such as EEG, using machine learning has been a challenge due to the small data-sets and difficulty to obtain labels. We propose a reconstruction-based self-supervised learning model, the masked auto-encoder for EEG (MAEEG), for learning EEG representations by learning to reconstruct the masked EEG features using a transformer architecture. We found that MAEEG can learn representations that significantly improve sleep stage classification (~5% accuracy increase) when only a small number of labels are given. We also found that input sample lengths and differ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.02625","kind":"arxiv","version":1},"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/2211.02625/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":"2026-07-05T05:13:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NDV3PkCYfauyGPHpPSjs4PfI2OktEMYMGm6aUVMIdL7r2ipKTV3wdKvglxr07FGPdHm2K1xYIw70tlmmeX0cDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:13:36.882435Z"},"content_sha256":"43cc52c7800edf65e8fe7f74da09b2997733056d8bf00308bb4fc1d60de66369","schema_version":"1.0","event_id":"sha256:43cc52c7800edf65e8fe7f74da09b2997733056d8bf00308bb4fc1d60de66369"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/bundle.json","state_url":"https://pith.science/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/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":"2026-08-09T05:13:36Z","links":{"resolver":"https://pith.science/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB","bundle":"https://pith.science/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/bundle.json","state":"https://pith.science/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4EVMLTBVP7Q3NHDPBJ7FP27OBB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:4EVMLTBVP7Q3NHDPBJ7FP27OBB","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":"707a4f1ef6189e7b985aeff08077c0492cee22990d8d8dfeb2342a19709f85a1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-27T21:43:35Z","title_canon_sha256":"f0ed2b4c625beb6aae07312e6309bb1aeaa7243aa822aded1b583be81ab09964"},"schema_version":"1.0","source":{"id":"2211.02625","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.02625","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"arxiv_version","alias_value":"2211.02625v1","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.02625","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_12","alias_value":"4EVMLTBVP7Q3","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_16","alias_value":"4EVMLTBVP7Q3NHDP","created_at":"2026-07-05T05:13:17Z"},{"alias_kind":"pith_short_8","alias_value":"4EVMLTBV","created_at":"2026-07-05T05:13:17Z"}],"graph_snapshots":[{"event_id":"sha256:43cc52c7800edf65e8fe7f74da09b2997733056d8bf00308bb4fc1d60de66369","target":"graph","created_at":"2026-07-05T05:13:17Z","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/2211.02625/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Decoding information from bio-signals such as EEG, using machine learning has been a challenge due to the small data-sets and difficulty to obtain labels. We propose a reconstruction-based self-supervised learning model, the masked auto-encoder for EEG (MAEEG), for learning EEG representations by learning to reconstruct the masked EEG features using a transformer architecture. We found that MAEEG can learn representations that significantly improve sleep stage classification (~5% accuracy increase) when only a small number of labels are given. We also found that input sample lengths and differ","authors_text":"Christopher M. Sandino, Hanlin Goh, Hsiang-Yun Sherry Chien, Joseph Y. Cheng","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-27T21:43:35Z","title":"MAEEG: Masked Auto-encoder for EEG Representation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.02625","kind":"arxiv","version":1},"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":"sha256:06007b25cf42491e15dd1297e38ae16256c2a8b76e590bc0aee6b93a07b7b47b","target":"record","created_at":"2026-07-05T05:13:17Z","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":"707a4f1ef6189e7b985aeff08077c0492cee22990d8d8dfeb2342a19709f85a1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-27T21:43:35Z","title_canon_sha256":"f0ed2b4c625beb6aae07312e6309bb1aeaa7243aa822aded1b583be81ab09964"},"schema_version":"1.0","source":{"id":"2211.02625","kind":"arxiv","version":1}},"canonical_sha256":"e12ac5cc357fe1b69c6f0a7e57ebee087be0ea6698d84085d3605df365865f3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e12ac5cc357fe1b69c6f0a7e57ebee087be0ea6698d84085d3605df365865f3a","first_computed_at":"2026-07-05T05:13:17.413931Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:13:17.413931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4FazYqLbZcNBn1aLJYtUYI1yZxBQpmQ7idt+xpUMLANNGEH0iI1tciUI+mBlfcB3cMOhPIXLi6dG6JUu+KGCDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:13:17.414352Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.02625","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:06007b25cf42491e15dd1297e38ae16256c2a8b76e590bc0aee6b93a07b7b47b","sha256:43cc52c7800edf65e8fe7f74da09b2997733056d8bf00308bb4fc1d60de66369"],"state_sha256":"23f55de5b5179f3b3d379911ce3e194e497248e10a4dea6c529c272691a73d72"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5owuDG+UPbfblLYa1n26ZrhPYa3m4aTgF/VASIok7rVxAGOLD5L/WWK320dapzr0Le7kzYBiV0WLj73RYGWpBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:13:36.888990Z","bundle_sha256":"e9d74df2bde4bcf1e667e5ee9349f8c48a79cf57a139c3bd9f7141dca0b890ff"}}