{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MF4N4Y6UZEXWMMXFZUUISWC665","short_pith_number":"pith:MF4N4Y6U","canonical_record":{"source":{"id":"2409.08010","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:55:49Z","cross_cats_sorted":[],"title_canon_sha256":"eed5643ba0e11b693c3a6484a2e82b4c52ac0b1f2abcbcd4a1b80de6380a9cdc","abstract_canon_sha256":"5ce85fd15fa523f335d6782757354368ff18104452f7cd41d2f0011c71ffb2c9"},"schema_version":"1.0"},"canonical_sha256":"6178de63d4c92f6632e5cd2889585ef77122ffca87dc134807458c0efe7f119f","source":{"kind":"arxiv","id":"2409.08010","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.08010","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2409.08010v1","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.08010","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"MF4N4Y6UZEXW","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"MF4N4Y6UZEXWMMXF","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"MF4N4Y6U","created_at":"2026-07-05T09:06:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MF4N4Y6UZEXWMMXFZUUISWC665","target":"record","payload":{"canonical_record":{"source":{"id":"2409.08010","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:55:49Z","cross_cats_sorted":[],"title_canon_sha256":"eed5643ba0e11b693c3a6484a2e82b4c52ac0b1f2abcbcd4a1b80de6380a9cdc","abstract_canon_sha256":"5ce85fd15fa523f335d6782757354368ff18104452f7cd41d2f0011c71ffb2c9"},"schema_version":"1.0"},"canonical_sha256":"6178de63d4c92f6632e5cd2889585ef77122ffca87dc134807458c0efe7f119f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:18.725807Z","signature_b64":"cp/0LO9SSYlOiUN88bJcHYuWEuPGvs3dQtRycOdEiGnBX2Dy5Pr2MFi90lhbLnx7GuolKY2UXflecbhz+L6sDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6178de63d4c92f6632e5cd2889585ef77122ffca87dc134807458c0efe7f119f","last_reissued_at":"2026-07-05T09:06:18.725329Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:18.725329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.08010","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":"2026-07-05T09:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2eeFj+nkIt+COPRAwy2aWWiumyIWhGoVk1w/L3THiDCkTpeoqk4t+X0SRTtYaQTrD3WM9nU1gtpb0krvmX1pDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T17:32:21.009835Z"},"content_sha256":"a8bb89df247fb37e7a910ff9c842e8b56b25defe1a812eae8582251451bddf49","schema_version":"1.0","event_id":"sha256:a8bb89df247fb37e7a910ff9c842e8b56b25defe1a812eae8582251451bddf49"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MF4N4Y6UZEXWMMXFZUUISWC665","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multiplex Graph Contrastive Learning with Soft Negatives","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chen Wang, Jiqiang Zhang, Li Chen, Minhong Zhu, Sijia Wang, Weiran Cai, Zhenhao Zhao","submitted_at":"2024-09-12T12:55:49Z","abstract_excerpt":"Graph Contrastive Learning (GCL) seeks to learn nodal or graph representations that contain maximal consistent information from graph-structured data. While node-level contrasting modes are dominating, some efforts commence to explore consistency across different scales. Yet, they tend to lose consistent information and be contaminated by disturbing features. Here, we introduce MUX-GCL, a novel cross-scale contrastive learning paradigm that utilizes multiplex representations as effective patches. While this learning mode minimizes contaminating noises, a commensurate contrasting strategy using"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.08010","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/2409.08010/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":"2026-07-05T09:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6NaghdvIs3nYSOPahlVWkGD0jblxowyhPjS8WwT7M564etstvaFeI2es+IjkHs0PaKT/MAvViponKU8vVuLVCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T17:32:21.010213Z"},"content_sha256":"ad836c8e6edb30fc060a20ec023e02e0e3d8eecc18022483e83e58030799040f","schema_version":"1.0","event_id":"sha256:ad836c8e6edb30fc060a20ec023e02e0e3d8eecc18022483e83e58030799040f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MF4N4Y6UZEXWMMXFZUUISWC665/bundle.json","state_url":"https://pith.science/pith/MF4N4Y6UZEXWMMXFZUUISWC665/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MF4N4Y6UZEXWMMXFZUUISWC665/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":"2026-07-18T17:32:21Z","links":{"resolver":"https://pith.science/pith/MF4N4Y6UZEXWMMXFZUUISWC665","bundle":"https://pith.science/pith/MF4N4Y6UZEXWMMXFZUUISWC665/bundle.json","state":"https://pith.science/pith/MF4N4Y6UZEXWMMXFZUUISWC665/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MF4N4Y6UZEXWMMXFZUUISWC665/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MF4N4Y6UZEXWMMXFZUUISWC665","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":"5ce85fd15fa523f335d6782757354368ff18104452f7cd41d2f0011c71ffb2c9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:55:49Z","title_canon_sha256":"eed5643ba0e11b693c3a6484a2e82b4c52ac0b1f2abcbcd4a1b80de6380a9cdc"},"schema_version":"1.0","source":{"id":"2409.08010","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.08010","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2409.08010v1","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.08010","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"MF4N4Y6UZEXW","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"MF4N4Y6UZEXWMMXF","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"MF4N4Y6U","created_at":"2026-07-05T09:06:18Z"}],"graph_snapshots":[{"event_id":"sha256:ad836c8e6edb30fc060a20ec023e02e0e3d8eecc18022483e83e58030799040f","target":"graph","created_at":"2026-07-05T09:06:18Z","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/2409.08010/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Contrastive Learning (GCL) seeks to learn nodal or graph representations that contain maximal consistent information from graph-structured data. While node-level contrasting modes are dominating, some efforts commence to explore consistency across different scales. Yet, they tend to lose consistent information and be contaminated by disturbing features. Here, we introduce MUX-GCL, a novel cross-scale contrastive learning paradigm that utilizes multiplex representations as effective patches. While this learning mode minimizes contaminating noises, a commensurate contrasting strategy using","authors_text":"Chen Wang, Jiqiang Zhang, Li Chen, Minhong Zhu, Sijia Wang, Weiran Cai, Zhenhao Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:55:49Z","title":"Multiplex Graph Contrastive Learning with Soft Negatives"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.08010","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:a8bb89df247fb37e7a910ff9c842e8b56b25defe1a812eae8582251451bddf49","target":"record","created_at":"2026-07-05T09:06:18Z","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":"5ce85fd15fa523f335d6782757354368ff18104452f7cd41d2f0011c71ffb2c9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:55:49Z","title_canon_sha256":"eed5643ba0e11b693c3a6484a2e82b4c52ac0b1f2abcbcd4a1b80de6380a9cdc"},"schema_version":"1.0","source":{"id":"2409.08010","kind":"arxiv","version":1}},"canonical_sha256":"6178de63d4c92f6632e5cd2889585ef77122ffca87dc134807458c0efe7f119f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6178de63d4c92f6632e5cd2889585ef77122ffca87dc134807458c0efe7f119f","first_computed_at":"2026-07-05T09:06:18.725329Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:06:18.725329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cp/0LO9SSYlOiUN88bJcHYuWEuPGvs3dQtRycOdEiGnBX2Dy5Pr2MFi90lhbLnx7GuolKY2UXflecbhz+L6sDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:06:18.725807Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.08010","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8bb89df247fb37e7a910ff9c842e8b56b25defe1a812eae8582251451bddf49","sha256:ad836c8e6edb30fc060a20ec023e02e0e3d8eecc18022483e83e58030799040f"],"state_sha256":"8cb30a1a3d4cef01a677f3e618518fbd82cbfefb58a324be20506ab29169a49b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FvrH7ejhJWdOxqWJcScMcN4bfLySe9b+NJZU6ul0nEHk62lvgLrS6zjOKlNpcilWq1WDG7J62gndSQ2tQkFhBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-18T17:32:21.013302Z","bundle_sha256":"e2e6913c4fb740e5b60ab45d1885f9899731fcfd40688e6af7d51c00cc2db437"}}