{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QXDFQPOC6IPDISGAA4XXJKNMT3","short_pith_number":"pith:QXDFQPOC","canonical_record":{"source":{"id":"2505.17972","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T14:40:50Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"98d169cb29fb1760c0b5b69a9f652f9ca2682850cbbbb01c023132af84a4428d","abstract_canon_sha256":"80e26438280e60731df53e631c11d85b2a6c224ab9ec688b4ebf5537308dca5e"},"schema_version":"1.0"},"canonical_sha256":"85c6583dc2f21e3448c0072f74a9ac9ef6deec9bd3b98896d2cf0d00f7af9506","source":{"kind":"arxiv","id":"2505.17972","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17972","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17972v2","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17972","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"QXDFQPOC6IPD","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"QXDFQPOC6IPDISGA","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"QXDFQPOC","created_at":"2026-07-05T11:55:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QXDFQPOC6IPDISGAA4XXJKNMT3","target":"record","payload":{"canonical_record":{"source":{"id":"2505.17972","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T14:40:50Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"98d169cb29fb1760c0b5b69a9f652f9ca2682850cbbbb01c023132af84a4428d","abstract_canon_sha256":"80e26438280e60731df53e631c11d85b2a6c224ab9ec688b4ebf5537308dca5e"},"schema_version":"1.0"},"canonical_sha256":"85c6583dc2f21e3448c0072f74a9ac9ef6deec9bd3b98896d2cf0d00f7af9506","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:55:40.116600Z","signature_b64":"PIsif0gMfzIiiXTt2Iv2Io6D69BlV75OhCf2V9toXYFEZ6U50k/nyN26Hvgb05/1b7FEbp1Rkxnvr2m1SjDrCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"85c6583dc2f21e3448c0072f74a9ac9ef6deec9bd3b98896d2cf0d00f7af9506","last_reissued_at":"2026-07-05T11:55:40.116017Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:55:40.116017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.17972","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lmzw3cLYfVI6KU7GERtQ0cthsomn/jBzA3n9qaIzHilDoeomM8suDxEaiexQR5xIdGAsAUMoI0RbV8TayO0pBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T10:20:41.225684Z"},"content_sha256":"8617273c817235b7fdff1aa85400676183b5e38c9ab6903882a1f702270978e0","schema_version":"1.0","event_id":"sha256:8617273c817235b7fdff1aa85400676183b5e38c9ab6903882a1f702270978e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QXDFQPOC6IPDISGAA4XXJKNMT3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MR-EEGWaveNet: Multiresolutional EEGWaveNet for Seizure Detection from Long EEG Recordings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Hidenori Sugano, Kazi Mahmudul Hassan, Toshihisa Tanaka, Xuyang Zhao","submitted_at":"2025-05-23T14:40:50Z","abstract_excerpt":"Feature engineering for generalized seizure detection models remains a significant challenge. Recently proposed models show variable performance depending on the training data and remain ineffective at accurately distinguishing artifacts from seizure data. In this study, we propose a novel end-to-end model, \"Multiresolutional EEGWaveNet (MR-EEGWaveNet),\" which efficiently distinguishes seizure events from background electroencephalogram (EEG) and artifacts/noise by capturing both temporal dependencies across different time frames and spatial relationships between channels. The model has three "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17972","kind":"arxiv","version":2},"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/2505.17972/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":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kB/XKJnSFhtkUExHSBWMV/C0pOKbdsVO5HtmdFFsJRb4ourYnaIODsZVGBHnGukBWv9bi6jmu3Q8BR2Jo4BbBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T10:20:41.226586Z"},"content_sha256":"9918cd5571ec2a0c41d23b8e0e9f89b6a6a1b8e6a869efb180bbb322ba1cfd0b","schema_version":"1.0","event_id":"sha256:9918cd5571ec2a0c41d23b8e0e9f89b6a6a1b8e6a869efb180bbb322ba1cfd0b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/bundle.json","state_url":"https://pith.science/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/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":"2026-08-12T10:20:41Z","links":{"resolver":"https://pith.science/pith/QXDFQPOC6IPDISGAA4XXJKNMT3","bundle":"https://pith.science/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/bundle.json","state":"https://pith.science/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QXDFQPOC6IPDISGAA4XXJKNMT3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QXDFQPOC6IPDISGAA4XXJKNMT3","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":"80e26438280e60731df53e631c11d85b2a6c224ab9ec688b4ebf5537308dca5e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T14:40:50Z","title_canon_sha256":"98d169cb29fb1760c0b5b69a9f652f9ca2682850cbbbb01c023132af84a4428d"},"schema_version":"1.0","source":{"id":"2505.17972","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17972","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17972v2","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17972","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"QXDFQPOC6IPD","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"QXDFQPOC6IPDISGA","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"QXDFQPOC","created_at":"2026-07-05T11:55:40Z"}],"graph_snapshots":[{"event_id":"sha256:9918cd5571ec2a0c41d23b8e0e9f89b6a6a1b8e6a869efb180bbb322ba1cfd0b","target":"graph","created_at":"2026-07-05T11:55:40Z","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/2505.17972/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Feature engineering for generalized seizure detection models remains a significant challenge. Recently proposed models show variable performance depending on the training data and remain ineffective at accurately distinguishing artifacts from seizure data. In this study, we propose a novel end-to-end model, \"Multiresolutional EEGWaveNet (MR-EEGWaveNet),\" which efficiently distinguishes seizure events from background electroencephalogram (EEG) and artifacts/noise by capturing both temporal dependencies across different time frames and spatial relationships between channels. The model has three ","authors_text":"Hidenori Sugano, Kazi Mahmudul Hassan, Toshihisa Tanaka, Xuyang Zhao","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T14:40:50Z","title":"MR-EEGWaveNet: Multiresolutional EEGWaveNet for Seizure Detection from Long EEG Recordings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17972","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":"sha256:8617273c817235b7fdff1aa85400676183b5e38c9ab6903882a1f702270978e0","target":"record","created_at":"2026-07-05T11:55:40Z","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":"80e26438280e60731df53e631c11d85b2a6c224ab9ec688b4ebf5537308dca5e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T14:40:50Z","title_canon_sha256":"98d169cb29fb1760c0b5b69a9f652f9ca2682850cbbbb01c023132af84a4428d"},"schema_version":"1.0","source":{"id":"2505.17972","kind":"arxiv","version":2}},"canonical_sha256":"85c6583dc2f21e3448c0072f74a9ac9ef6deec9bd3b98896d2cf0d00f7af9506","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85c6583dc2f21e3448c0072f74a9ac9ef6deec9bd3b98896d2cf0d00f7af9506","first_computed_at":"2026-07-05T11:55:40.116017Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:55:40.116017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PIsif0gMfzIiiXTt2Iv2Io6D69BlV75OhCf2V9toXYFEZ6U50k/nyN26Hvgb05/1b7FEbp1Rkxnvr2m1SjDrCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:55:40.116600Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17972","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8617273c817235b7fdff1aa85400676183b5e38c9ab6903882a1f702270978e0","sha256:9918cd5571ec2a0c41d23b8e0e9f89b6a6a1b8e6a869efb180bbb322ba1cfd0b"],"state_sha256":"afb1e783b2eef5f0eb72fe0a9ea9ab4e8206be41bac5d57bb7c1d747af00efcc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"34vdkr7NS9EkPJzs5eAGOlidjqwwrsVHpwNkK1/Zi01xOYOlKjrG6E4ocuF708vda0NkOjWLrDjmo7bhqXisCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T10:20:41.233982Z","bundle_sha256":"afb89e9e139104c5aedae53b8f5899956960a9f7affdbb9ecf5a92e80acc64b2"}}