{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:UY3N5HBBJ3EMZARVS4KM7XQOL2","short_pith_number":"pith:UY3N5HBB","canonical_record":{"source":{"id":"2110.02027","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-10-05T13:15:59Z","cross_cats_sorted":[],"title_canon_sha256":"3f1f4d5a170631af885da27cd602820f1f562b1a3a908175ab09d3b75caeebdd","abstract_canon_sha256":"7e354097c562443522fe48bd36eecb9b05bb1313bbfefc48ea027cdb91f6c3b5"},"schema_version":"1.0"},"canonical_sha256":"a636de9c214ec8cc82359714cfde0e5ea5375b3f16fa71e0bf03bb192321115e","source":{"kind":"arxiv","id":"2110.02027","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02027","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02027v3","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02027","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_12","alias_value":"UY3N5HBBJ3EM","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_16","alias_value":"UY3N5HBBJ3EMZARV","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_8","alias_value":"UY3N5HBB","created_at":"2026-07-05T04:31:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:UY3N5HBBJ3EMZARVS4KM7XQOL2","target":"record","payload":{"canonical_record":{"source":{"id":"2110.02027","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-10-05T13:15:59Z","cross_cats_sorted":[],"title_canon_sha256":"3f1f4d5a170631af885da27cd602820f1f562b1a3a908175ab09d3b75caeebdd","abstract_canon_sha256":"7e354097c562443522fe48bd36eecb9b05bb1313bbfefc48ea027cdb91f6c3b5"},"schema_version":"1.0"},"canonical_sha256":"a636de9c214ec8cc82359714cfde0e5ea5375b3f16fa71e0bf03bb192321115e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:31:25.325309Z","signature_b64":"0FSdlo2Rpf3FzAiWCGqqruv2gkqRSi8Lx0w79+STr5c72bw0RgITvFne7HpWsP2V0391sSEexpm50MUGS9zCAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a636de9c214ec8cc82359714cfde0e5ea5375b3f16fa71e0bf03bb192321115e","last_reissued_at":"2026-07-05T04:31:25.324879Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:31:25.324879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.02027","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:31:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lGV9qKHNthv4VNC5Ee9xcG9dG7ZUwNOPsCF1iZT1b10ThymcBmV7eIn8tqK+McYXeS1Y6RG35aHPGiFiCRxxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T09:28:29.153687Z"},"content_sha256":"edb29de3cee4991b5c3a6702a348a807014602f4a8c2ececc45bb92846e968f1","schema_version":"1.0","event_id":"sha256:edb29de3cee4991b5c3a6702a348a807014602f4a8c2ececc45bb92846e968f1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:UY3N5HBBJ3EMZARVS4KM7XQOL2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ge Wang, Jintao Chen, Jun Xia, Lirong Wu, Stan Z.Li","submitted_at":"2021-10-05T13:15:59Z","abstract_excerpt":"Contrastive Learning (CL) has emerged as a dominant technique for unsupervised representation learning which embeds augmented versions of the anchor close to each other (positive samples) and pushes the embeddings of other samples (negatives) apart. As revealed in recent studies, CL can benefit from hard negatives (negatives that are most similar to the anchor). However, we observe limited benefits when we adopt existing hard negative mining techniques of other domains in Graph Contrastive Learning (GCL). We perform both experimental and theoretical analysis on this phenomenon and find it can "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02027","kind":"arxiv","version":3},"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/2110.02027/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":"2026-07-05T04:31:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HmYVnlZtBzRNVsKQ6zvE0LsjJhSDVjA/e25gYK9kAXiRDX0PWQOCq+MnXb0tyvlLTG0t4tbHUwY+fLNyVK0KAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T09:28:29.154203Z"},"content_sha256":"7670574be645f8fb242aa627daef08e4f37b4e404aad556378aad63eddf5a711","schema_version":"1.0","event_id":"sha256:7670574be645f8fb242aa627daef08e4f37b4e404aad556378aad63eddf5a711"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/bundle.json","state_url":"https://pith.science/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/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":"2026-08-07T09:28:29Z","links":{"resolver":"https://pith.science/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2","bundle":"https://pith.science/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/bundle.json","state":"https://pith.science/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UY3N5HBBJ3EMZARVS4KM7XQOL2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:UY3N5HBBJ3EMZARVS4KM7XQOL2","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":"7e354097c562443522fe48bd36eecb9b05bb1313bbfefc48ea027cdb91f6c3b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-10-05T13:15:59Z","title_canon_sha256":"3f1f4d5a170631af885da27cd602820f1f562b1a3a908175ab09d3b75caeebdd"},"schema_version":"1.0","source":{"id":"2110.02027","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02027","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02027v3","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02027","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_12","alias_value":"UY3N5HBBJ3EM","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_16","alias_value":"UY3N5HBBJ3EMZARV","created_at":"2026-07-05T04:31:25Z"},{"alias_kind":"pith_short_8","alias_value":"UY3N5HBB","created_at":"2026-07-05T04:31:25Z"}],"graph_snapshots":[{"event_id":"sha256:7670574be645f8fb242aa627daef08e4f37b4e404aad556378aad63eddf5a711","target":"graph","created_at":"2026-07-05T04:31:25Z","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/2110.02027/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Contrastive Learning (CL) has emerged as a dominant technique for unsupervised representation learning which embeds augmented versions of the anchor close to each other (positive samples) and pushes the embeddings of other samples (negatives) apart. As revealed in recent studies, CL can benefit from hard negatives (negatives that are most similar to the anchor). However, we observe limited benefits when we adopt existing hard negative mining techniques of other domains in Graph Contrastive Learning (GCL). We perform both experimental and theoretical analysis on this phenomenon and find it can ","authors_text":"Ge Wang, Jintao Chen, Jun Xia, Lirong Wu, Stan Z.Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-10-05T13:15:59Z","title":"ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02027","kind":"arxiv","version":3},"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:edb29de3cee4991b5c3a6702a348a807014602f4a8c2ececc45bb92846e968f1","target":"record","created_at":"2026-07-05T04:31:25Z","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":"7e354097c562443522fe48bd36eecb9b05bb1313bbfefc48ea027cdb91f6c3b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-10-05T13:15:59Z","title_canon_sha256":"3f1f4d5a170631af885da27cd602820f1f562b1a3a908175ab09d3b75caeebdd"},"schema_version":"1.0","source":{"id":"2110.02027","kind":"arxiv","version":3}},"canonical_sha256":"a636de9c214ec8cc82359714cfde0e5ea5375b3f16fa71e0bf03bb192321115e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a636de9c214ec8cc82359714cfde0e5ea5375b3f16fa71e0bf03bb192321115e","first_computed_at":"2026-07-05T04:31:25.324879Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:31:25.324879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0FSdlo2Rpf3FzAiWCGqqruv2gkqRSi8Lx0w79+STr5c72bw0RgITvFne7HpWsP2V0391sSEexpm50MUGS9zCAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:31:25.325309Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.02027","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:edb29de3cee4991b5c3a6702a348a807014602f4a8c2ececc45bb92846e968f1","sha256:7670574be645f8fb242aa627daef08e4f37b4e404aad556378aad63eddf5a711"],"state_sha256":"b86421457f376c3d7137a8700476124b3fe6e2d7680e38cc4288cab82bb64b83"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"poR7I+Dxol6aE51okKVefWfMhvwx8NgutpqkjUxff/7TGEyMkeDFKRvea7oWr8im9BjURrnQ69YjHQgSPN9RDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T09:28:29.158938Z","bundle_sha256":"87d7ea1e1d163c01a5cdbbc1f8a487330ed8f587e8769d99873e2c31dbf2e7e0"}}