{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:BEJJZF5LZW37MDNJ2VE3QXUTCG","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":"199d8b915a8f0f47a55b44f615b10346c1f6c0ff1172126ec0ec21fc98b00571","cross_cats_sorted":["cs.AI","eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T10:37:03Z","title_canon_sha256":"5f4ec9f00d73b4aaa87101aa03d1775980da42ec8ed47adaba52c4ea477b5976"},"schema_version":"1.0","source":{"id":"2102.04456","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.04456","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"arxiv_version","alias_value":"2102.04456v1","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.04456","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_12","alias_value":"BEJJZF5LZW37","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_16","alias_value":"BEJJZF5LZW37MDNJ","created_at":"2026-07-05T02:13:34Z"},{"alias_kind":"pith_short_8","alias_value":"BEJJZF5L","created_at":"2026-07-05T02:13:34Z"}],"graph_snapshots":[{"event_id":"sha256:add55773e2d8f56005006170d433be9e4ce2678e075935466d007e496d3bf729","target":"graph","created_at":"2026-07-05T02:13:34Z","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/2102.04456/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The cross-subject application of EEG-based brain-computer interface (BCI) has always been limited by large individual difference and complex characteristics that are difficult to perceive. Therefore, it takes a long time to collect the training data of each user for calibration. Even transfer learning method pre-training with amounts of subject-independent data cannot decode different EEG signal categories without enough subject-specific data. Hence, we proposed a cross-subject EEG classification framework with a generative adversarial networks (GANs) based method named common spatial GAN (CS-","authors_text":"Lie Yang, Longhan Xie, Xueyu Jia, Yonghao Song","cross_cats":["cs.AI","eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T10:37:03Z","title":"Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.04456","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":"sha256:68968956de775e8acef4d040cf71948e1ea42026f9f4d6e0e9df737cb8ba6028","target":"record","created_at":"2026-07-05T02:13:34Z","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":"199d8b915a8f0f47a55b44f615b10346c1f6c0ff1172126ec0ec21fc98b00571","cross_cats_sorted":["cs.AI","eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T10:37:03Z","title_canon_sha256":"5f4ec9f00d73b4aaa87101aa03d1775980da42ec8ed47adaba52c4ea477b5976"},"schema_version":"1.0","source":{"id":"2102.04456","kind":"arxiv","version":1}},"canonical_sha256":"09129c97abcdb7f60da9d549b85e9311abd7052c3693f6bc167320dc0c372827","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"09129c97abcdb7f60da9d549b85e9311abd7052c3693f6bc167320dc0c372827","first_computed_at":"2026-07-05T02:13:34.387484Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:13:34.387484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NbaTmTvVOWWtXn3oO+wsp01nFNVawe2eSuBfrmU2yEl2zDOMGu5MH60uLAncBQIy+SvsBkQ6D33pO9I1q7xHCg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:13:34.387929Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.04456","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68968956de775e8acef4d040cf71948e1ea42026f9f4d6e0e9df737cb8ba6028","sha256:add55773e2d8f56005006170d433be9e4ce2678e075935466d007e496d3bf729"],"state_sha256":"1cdb8b2bd41657a6bbfd49a6f4dcc5c545e8ac092d4a94efb500d7fada595fb9"}