{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:CH6O3ZWQKLWJXPDL53AXMAF5CI","short_pith_number":"pith:CH6O3ZWQ","canonical_record":{"source":{"id":"2504.18148","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-25T08:00:38Z","cross_cats_sorted":[],"title_canon_sha256":"c6746b7fdf2b71623129fdcef105457af205119209752b8988d39234a51df6ff","abstract_canon_sha256":"6b9444d4584a4382e95d63237863c63ed2934d536cb1ab96686cd8f1a2fec538"},"schema_version":"1.0"},"canonical_sha256":"11fcede6d052ec9bbc6beec17600bd1232c355ccadeab4e8ffb036e11c8f0ef2","source":{"kind":"arxiv","id":"2504.18148","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.18148","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"arxiv_version","alias_value":"2504.18148v1","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.18148","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_12","alias_value":"CH6O3ZWQKLWJ","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_16","alias_value":"CH6O3ZWQKLWJXPDL","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_8","alias_value":"CH6O3ZWQ","created_at":"2026-07-05T10:54:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:CH6O3ZWQKLWJXPDL53AXMAF5CI","target":"record","payload":{"canonical_record":{"source":{"id":"2504.18148","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-25T08:00:38Z","cross_cats_sorted":[],"title_canon_sha256":"c6746b7fdf2b71623129fdcef105457af205119209752b8988d39234a51df6ff","abstract_canon_sha256":"6b9444d4584a4382e95d63237863c63ed2934d536cb1ab96686cd8f1a2fec538"},"schema_version":"1.0"},"canonical_sha256":"11fcede6d052ec9bbc6beec17600bd1232c355ccadeab4e8ffb036e11c8f0ef2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:54:02.706224Z","signature_b64":"kW7bL2NodeyFabqmbs6Lu3CUxQj/5tQDJzS/I8gqYOQOO2KaSm++Lt9n6/lYDN+Xl1fNbNC46p/NoyfJafY+DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"11fcede6d052ec9bbc6beec17600bd1232c355ccadeab4e8ffb036e11c8f0ef2","last_reissued_at":"2026-07-05T10:54:02.705693Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:54:02.705693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.18148","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":"2026-07-05T10:54:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"44n5ajR4iLQdR4kT+m5oo7IooJ/NRmDovmAuqLP1458N6FPaEnczSlVLiKkWOokb9Xw5DidQ9v/MaWBLvnXpDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T16:16:35.473264Z"},"content_sha256":"b9a6c14512bd3b4e682731df40b390f74729dcde197649f75759ff372d0809d9","schema_version":"1.0","event_id":"sha256:b9a6c14512bd3b4e682731df40b390f74729dcde197649f75759ff372d0809d9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:CH6O3ZWQKLWJXPDL53AXMAF5CI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Generative Graph Contrastive Learning Model with Global Signal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Binyan Zhang, Xiaofan Wei","submitted_at":"2025-04-25T08:00:38Z","abstract_excerpt":"Graph contrastive learning (GCL) has garnered significant attention recently since it learns complex structural information from graphs through self-supervised learning manner. However, prevalent GCL models may suffer from performance degradation due to inappropriate contrastive signals. Concretely, they commonly generate augmented views based on random perturbation, which leads to biased essential structures due to the introduction of noise. In addition, they assign equal weight to both hard and easy sample pairs, thereby ignoring the difference in importance of the sample pairs. To address t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.18148","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/2504.18148/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":"2026-07-05T10:54:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UeUBClMD87PVUIt0MfTSQ5tBfgJWXNZz6+PC0isvI1xOjWTibfPv/l73cROqInf1w5I5497ht/vJ3GYZuWfKDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T16:16:35.474032Z"},"content_sha256":"4dc30daac57ab46922059f42b3dc87dd64a6fcccbfc64a462f716fda6b33b7a6","schema_version":"1.0","event_id":"sha256:4dc30daac57ab46922059f42b3dc87dd64a6fcccbfc64a462f716fda6b33b7a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/bundle.json","state_url":"https://pith.science/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/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":"2026-08-20T16:16:35Z","links":{"resolver":"https://pith.science/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI","bundle":"https://pith.science/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/bundle.json","state":"https://pith.science/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CH6O3ZWQKLWJXPDL53AXMAF5CI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CH6O3ZWQKLWJXPDL53AXMAF5CI","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":"6b9444d4584a4382e95d63237863c63ed2934d536cb1ab96686cd8f1a2fec538","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-25T08:00:38Z","title_canon_sha256":"c6746b7fdf2b71623129fdcef105457af205119209752b8988d39234a51df6ff"},"schema_version":"1.0","source":{"id":"2504.18148","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.18148","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"arxiv_version","alias_value":"2504.18148v1","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.18148","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_12","alias_value":"CH6O3ZWQKLWJ","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_16","alias_value":"CH6O3ZWQKLWJXPDL","created_at":"2026-07-05T10:54:02Z"},{"alias_kind":"pith_short_8","alias_value":"CH6O3ZWQ","created_at":"2026-07-05T10:54:02Z"}],"graph_snapshots":[{"event_id":"sha256:4dc30daac57ab46922059f42b3dc87dd64a6fcccbfc64a462f716fda6b33b7a6","target":"graph","created_at":"2026-07-05T10:54:02Z","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/2504.18148/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph contrastive learning (GCL) has garnered significant attention recently since it learns complex structural information from graphs through self-supervised learning manner. However, prevalent GCL models may suffer from performance degradation due to inappropriate contrastive signals. Concretely, they commonly generate augmented views based on random perturbation, which leads to biased essential structures due to the introduction of noise. In addition, they assign equal weight to both hard and easy sample pairs, thereby ignoring the difference in importance of the sample pairs. To address t","authors_text":"Binyan Zhang, Xiaofan Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-25T08:00:38Z","title":"A Generative Graph Contrastive Learning Model with Global Signal"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.18148","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:b9a6c14512bd3b4e682731df40b390f74729dcde197649f75759ff372d0809d9","target":"record","created_at":"2026-07-05T10:54:02Z","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":"6b9444d4584a4382e95d63237863c63ed2934d536cb1ab96686cd8f1a2fec538","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-25T08:00:38Z","title_canon_sha256":"c6746b7fdf2b71623129fdcef105457af205119209752b8988d39234a51df6ff"},"schema_version":"1.0","source":{"id":"2504.18148","kind":"arxiv","version":1}},"canonical_sha256":"11fcede6d052ec9bbc6beec17600bd1232c355ccadeab4e8ffb036e11c8f0ef2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"11fcede6d052ec9bbc6beec17600bd1232c355ccadeab4e8ffb036e11c8f0ef2","first_computed_at":"2026-07-05T10:54:02.705693Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:02.705693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kW7bL2NodeyFabqmbs6Lu3CUxQj/5tQDJzS/I8gqYOQOO2KaSm++Lt9n6/lYDN+Xl1fNbNC46p/NoyfJafY+DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:02.706224Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.18148","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9a6c14512bd3b4e682731df40b390f74729dcde197649f75759ff372d0809d9","sha256:4dc30daac57ab46922059f42b3dc87dd64a6fcccbfc64a462f716fda6b33b7a6"],"state_sha256":"9296a26ad17a45bb5f9ffea1c83951d01ffdfa5d32ae1ea9034a06c730509a06"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"byfLFzDKz4l4WKELRkzOIOoK1TPMheU/25ZcL31nYj/XLEOjvjqCauKaM05ZteK6fzWQ0DvJ/WOGdE9XLdM2Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T16:16:35.479605Z","bundle_sha256":"41749ca57ceb0035a2e6c83b3cd83017d54eebf3af51c7a3ceb918417731631a"}}