{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:MQXKX5FDC5HQDA6L2ZYNU62BZW","short_pith_number":"pith:MQXKX5FD","canonical_record":{"source":{"id":"2111.03262","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-05T05:08:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"01aaa45accfc8b8733ce650db5959a30159dfa1ffd60f3d3e74c5690f2982c6e","abstract_canon_sha256":"f09ae1de0a4330249f34331c49507844e79d74c726759ad75ebfcb5be52a7325"},"schema_version":"1.0"},"canonical_sha256":"642eabf4a3174f0183cbd670da7b41cd8b2c6b5250fd4533073ddbf559856d76","source":{"kind":"arxiv","id":"2111.03262","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.03262","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"arxiv_version","alias_value":"2111.03262v2","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.03262","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_12","alias_value":"MQXKX5FDC5HQ","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_16","alias_value":"MQXKX5FDC5HQDA6L","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_8","alias_value":"MQXKX5FD","created_at":"2026-07-05T08:02:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:MQXKX5FDC5HQDA6L2ZYNU62BZW","target":"record","payload":{"canonical_record":{"source":{"id":"2111.03262","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-05T05:08:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"01aaa45accfc8b8733ce650db5959a30159dfa1ffd60f3d3e74c5690f2982c6e","abstract_canon_sha256":"f09ae1de0a4330249f34331c49507844e79d74c726759ad75ebfcb5be52a7325"},"schema_version":"1.0"},"canonical_sha256":"642eabf4a3174f0183cbd670da7b41cd8b2c6b5250fd4533073ddbf559856d76","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:02:40.667052Z","signature_b64":"4K6YlLE5FuUpKIezcLXCuCmoAmQFsu5q4orwLR5Lsdt+l3chHqL2RevgGBNprQ0RaxhXwgeHkhrePGghhBxeAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"642eabf4a3174f0183cbd670da7b41cd8b2c6b5250fd4533073ddbf559856d76","last_reissued_at":"2026-07-05T08:02:40.666585Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:02:40.666585Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.03262","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":"2026-07-05T08:02:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3oVG045qhMsMUkrUzXjkADw1nwAPZ2uyuZteP2ttw4e45D0aHfmR8saai7bq9TtK7QPTnAeDDcroGIu0KXOnBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:47:08.757353Z"},"content_sha256":"af4b098e26fd5fea2bbaeb022ddf6806fb5d7be560c5c8c55102f77943abda28","schema_version":"1.0","event_id":"sha256:af4b098e26fd5fea2bbaeb022ddf6806fb5d7be560c5c8c55102f77943abda28"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:MQXKX5FDC5HQDA6L2ZYNU62BZW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Tianyu Zhang, Weitao Du, Wenzheng Feng, Xuecang Zhang, Yuxiang Ren","submitted_at":"2021-11-05T05:08:27Z","abstract_excerpt":"Unsupervised graph representation learning is a non-trivial topic. The success of contrastive methods in the unsupervised representation learning on structured data inspires similar attempts on the graph. Existing graph contrastive learning (GCL) aims to learn the invariance across multiple augmentation views, which renders it heavily reliant on the handcrafted graph augmentations. However, inappropriate graph data augmentations can potentially jeopardize such invariance. In this paper, we show the potential hazards of inappropriate augmentations and then propose a novel Collaborative Graph Co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.03262","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/2111.03262/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":"2026-07-05T08:02:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HV4wzaXsUmj8VdlD9XON7/8OtaGUmZ0TFn8UsxTyNPf2KaPIcCO/k/5oOuYiekUNPVWm6Jkl4EVFwGhN1NShBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:47:08.757730Z"},"content_sha256":"11e4e96ee7a5eacd6c84fa3b9c89f6433caa9f6e35ed25a11d89ffab630ab939","schema_version":"1.0","event_id":"sha256:11e4e96ee7a5eacd6c84fa3b9c89f6433caa9f6e35ed25a11d89ffab630ab939"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/bundle.json","state_url":"https://pith.science/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/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":"2026-07-07T14:47:08Z","links":{"resolver":"https://pith.science/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW","bundle":"https://pith.science/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/bundle.json","state":"https://pith.science/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQXKX5FDC5HQDA6L2ZYNU62BZW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:MQXKX5FDC5HQDA6L2ZYNU62BZW","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":"f09ae1de0a4330249f34331c49507844e79d74c726759ad75ebfcb5be52a7325","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-05T05:08:27Z","title_canon_sha256":"01aaa45accfc8b8733ce650db5959a30159dfa1ffd60f3d3e74c5690f2982c6e"},"schema_version":"1.0","source":{"id":"2111.03262","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.03262","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"arxiv_version","alias_value":"2111.03262v2","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.03262","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_12","alias_value":"MQXKX5FDC5HQ","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_16","alias_value":"MQXKX5FDC5HQDA6L","created_at":"2026-07-05T08:02:40Z"},{"alias_kind":"pith_short_8","alias_value":"MQXKX5FD","created_at":"2026-07-05T08:02:40Z"}],"graph_snapshots":[{"event_id":"sha256:11e4e96ee7a5eacd6c84fa3b9c89f6433caa9f6e35ed25a11d89ffab630ab939","target":"graph","created_at":"2026-07-05T08:02:40Z","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/2111.03262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unsupervised graph representation learning is a non-trivial topic. The success of contrastive methods in the unsupervised representation learning on structured data inspires similar attempts on the graph. Existing graph contrastive learning (GCL) aims to learn the invariance across multiple augmentation views, which renders it heavily reliant on the handcrafted graph augmentations. However, inappropriate graph data augmentations can potentially jeopardize such invariance. In this paper, we show the potential hazards of inappropriate augmentations and then propose a novel Collaborative Graph Co","authors_text":"Tianyu Zhang, Weitao Du, Wenzheng Feng, Xuecang Zhang, Yuxiang Ren","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-05T05:08:27Z","title":"CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.03262","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:af4b098e26fd5fea2bbaeb022ddf6806fb5d7be560c5c8c55102f77943abda28","target":"record","created_at":"2026-07-05T08:02:40Z","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":"f09ae1de0a4330249f34331c49507844e79d74c726759ad75ebfcb5be52a7325","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-05T05:08:27Z","title_canon_sha256":"01aaa45accfc8b8733ce650db5959a30159dfa1ffd60f3d3e74c5690f2982c6e"},"schema_version":"1.0","source":{"id":"2111.03262","kind":"arxiv","version":2}},"canonical_sha256":"642eabf4a3174f0183cbd670da7b41cd8b2c6b5250fd4533073ddbf559856d76","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"642eabf4a3174f0183cbd670da7b41cd8b2c6b5250fd4533073ddbf559856d76","first_computed_at":"2026-07-05T08:02:40.666585Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:40.666585Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4K6YlLE5FuUpKIezcLXCuCmoAmQFsu5q4orwLR5Lsdt+l3chHqL2RevgGBNprQ0RaxhXwgeHkhrePGghhBxeAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:40.667052Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.03262","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af4b098e26fd5fea2bbaeb022ddf6806fb5d7be560c5c8c55102f77943abda28","sha256:11e4e96ee7a5eacd6c84fa3b9c89f6433caa9f6e35ed25a11d89ffab630ab939"],"state_sha256":"0ec6096b7f9cd180733a15ff78b1053595fb47063cec934fd221caf06f48c06e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hWBbRDsifqp0jz9My6csFf1vihVsodqQb8gXqkdwV3ZndOcMTO/ih1U/Vdl1PhsmmSRHxugKEipVKNFc+zw8Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T14:47:08.759699Z","bundle_sha256":"d0c0f164891798a632d130119ceaf012e4ad2e96b998d2e2e1eaa04f3e0ae53b"}}