{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VSTU3DOOJUB4ZQR4TZ3X2O2ZPZ","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":"32ed820a1032eea16a26e03a35c080a65047d83346493209a40e6b60abc78606","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-28T15:53:32Z","title_canon_sha256":"8bbe55e47a4c22dc4b8293a472671d76742f28da7431d1dec9ae9e31c3cc8d36"},"schema_version":"1.0","source":{"id":"2411.19230","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.19230","created_at":"2026-07-05T11:33:17Z"},{"alias_kind":"arxiv_version","alias_value":"2411.19230v2","created_at":"2026-07-05T11:33:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.19230","created_at":"2026-07-05T11:33:17Z"},{"alias_kind":"pith_short_12","alias_value":"VSTU3DOOJUB4","created_at":"2026-07-05T11:33:17Z"},{"alias_kind":"pith_short_16","alias_value":"VSTU3DOOJUB4ZQR4","created_at":"2026-07-05T11:33:17Z"},{"alias_kind":"pith_short_8","alias_value":"VSTU3DOO","created_at":"2026-07-05T11:33:17Z"}],"graph_snapshots":[{"event_id":"sha256:6cb57df98083d3d24e479454f0df02dbbc81c566866a85335d82e1815cc1f23b","target":"graph","created_at":"2026-07-05T11:33:17Z","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/2411.19230/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Effectively utilizing extensive unlabeled high-density EEG data to improve performance in scenarios with limited labeled low-density EEG data presents a significant challenge. In this paper, we address this challenge by formulating it as a graph transfer learning and knowledge distillation problem. We propose a Unified Pre-trained Graph Contrastive Masked Autoencoder Distiller, named EEG-DisGCMAE, to bridge the gap between unlabeled and labeled as well as high- and low-density EEG data. Our approach introduces a novel unified graph self-supervised pre-training paradigm, which seamlessly integr","authors_text":"Hua Xie, Kanhao Zhao, Lifang He, Xinxu Wei, Yong Jiao, Yu Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-28T15:53:32Z","title":"Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.19230","kind":"arxiv","version":2},"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:b85eb7e764292020eb5fe9ff85a91d5085d28a8288326d0c3220b0b57ef3a672","target":"record","created_at":"2026-07-05T11:33:17Z","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":"32ed820a1032eea16a26e03a35c080a65047d83346493209a40e6b60abc78606","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-28T15:53:32Z","title_canon_sha256":"8bbe55e47a4c22dc4b8293a472671d76742f28da7431d1dec9ae9e31c3cc8d36"},"schema_version":"1.0","source":{"id":"2411.19230","kind":"arxiv","version":2}},"canonical_sha256":"aca74d8dce4d03ccc23c9e777d3b597e4b53e67c59ddddc47e1cd715d8f0a483","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aca74d8dce4d03ccc23c9e777d3b597e4b53e67c59ddddc47e1cd715d8f0a483","first_computed_at":"2026-07-05T11:33:17.921425Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:33:17.921425Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0uiB4bf2lNIif7DJYpRKB1fIou1jt7FtBTQNJRmdlD2RFXjZ/LOCPrSObU57Uaokv1XVGvHOPpijicKXSnU5Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:33:17.921855Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.19230","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b85eb7e764292020eb5fe9ff85a91d5085d28a8288326d0c3220b0b57ef3a672","sha256:6cb57df98083d3d24e479454f0df02dbbc81c566866a85335d82e1815cc1f23b"],"state_sha256":"e8f2b6a973b199aa116a7dee611b3ce5e878d276b7399f7dd7a8ee2110f0bd92"}