{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:CQA6IU5N5IXXYD2GKNXEUYOCLB","short_pith_number":"pith:CQA6IU5N","canonical_record":{"source":{"id":"2212.01026","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-02T08:48:11Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"8605092b9ab88fb0be1b03b986f205f17b06b10c187b2fc19cf9339f3590bcb6","abstract_canon_sha256":"75a6435d91f027257b1271655b5c10225ddbfd9a82a53108c5862df23392b027"},"schema_version":"1.0"},"canonical_sha256":"1401e453adea2f7c0f46536e4a61c2585269934865ef07c94451b69aa4a64169","source":{"kind":"arxiv","id":"2212.01026","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.01026","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"arxiv_version","alias_value":"2212.01026v1","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.01026","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_12","alias_value":"CQA6IU5N5IXX","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_16","alias_value":"CQA6IU5N5IXXYD2G","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_8","alias_value":"CQA6IU5N","created_at":"2026-07-05T05:21:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:CQA6IU5N5IXXYD2GKNXEUYOCLB","target":"record","payload":{"canonical_record":{"source":{"id":"2212.01026","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-02T08:48:11Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"8605092b9ab88fb0be1b03b986f205f17b06b10c187b2fc19cf9339f3590bcb6","abstract_canon_sha256":"75a6435d91f027257b1271655b5c10225ddbfd9a82a53108c5862df23392b027"},"schema_version":"1.0"},"canonical_sha256":"1401e453adea2f7c0f46536e4a61c2585269934865ef07c94451b69aa4a64169","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:21:48.723388Z","signature_b64":"3DmNysXF0GwG2t95sW9xv9VDTfEGs9VgxRh0nHECLtxPU1Gb0YYzKwgQ5ZmSxfaap9cUwDxsI/qN5RjupCpnCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1401e453adea2f7c0f46536e4a61c2585269934865ef07c94451b69aa4a64169","last_reissued_at":"2026-07-05T05:21:48.722924Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:21:48.722924Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.01026","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":"2026-07-05T05:21:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nmiWF8c6Sdc47qXColx/CkVWE45lkxfwHzxAcv3fxYpiiX42JvgS7NA2SIHQ98nG7a8CqAIqTX+kf3LVHp3UAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T06:13:15.462002Z"},"content_sha256":"2e07d1f6b439e7f5b5320591152fa26f8cc7a9f140b7dfdbc23eadd6f88d1d4f","schema_version":"1.0","event_id":"sha256:2e07d1f6b439e7f5b5320591152fa26f8cc7a9f140b7dfdbc23eadd6f88d1d4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:CQA6IU5N5IXXYD2GKNXEUYOCLB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spectral Feature Augmentation for Graph Contrastive Learning and Beyond","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Hao Zhu, Irwin King, Piotr Koniusz, Yifei Zhang, Zixing Song","submitted_at":"2022-12-02T08:48:11Z","abstract_excerpt":"Although augmentations (e.g., perturbation of graph edges, image crops) boost the efficiency of Contrastive Learning (CL), feature level augmentation is another plausible, complementary yet not well researched strategy. Thus, we present a novel spectral feature argumentation for contrastive learning on graphs (and images). To this end, for each data view, we estimate a low-rank approximation per feature map and subtract that approximation from the map to obtain its complement. This is achieved by the proposed herein incomplete power iteration, a non-standard power iteration regime which enjoys"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.01026","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/2212.01026/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":"2026-07-05T05:21:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5bHgf7zpOPbeXiqcrSJywD1oZygiMxmpEqPMrEJwdaISLI8AE89OkQwv0iTckeLn2QvAbeob1z1cJ2XbdwxSBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T06:13:15.462549Z"},"content_sha256":"7e7a5d042ab7abecdafd725110afa73cc24e53a6fcba0a841c1ea21f080b1961","schema_version":"1.0","event_id":"sha256:7e7a5d042ab7abecdafd725110afa73cc24e53a6fcba0a841c1ea21f080b1961"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/bundle.json","state_url":"https://pith.science/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/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":"2026-08-19T06:13:15Z","links":{"resolver":"https://pith.science/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB","bundle":"https://pith.science/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/bundle.json","state":"https://pith.science/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CQA6IU5N5IXXYD2GKNXEUYOCLB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:CQA6IU5N5IXXYD2GKNXEUYOCLB","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":"75a6435d91f027257b1271655b5c10225ddbfd9a82a53108c5862df23392b027","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-02T08:48:11Z","title_canon_sha256":"8605092b9ab88fb0be1b03b986f205f17b06b10c187b2fc19cf9339f3590bcb6"},"schema_version":"1.0","source":{"id":"2212.01026","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.01026","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"arxiv_version","alias_value":"2212.01026v1","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.01026","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_12","alias_value":"CQA6IU5N5IXX","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_16","alias_value":"CQA6IU5N5IXXYD2G","created_at":"2026-07-05T05:21:48Z"},{"alias_kind":"pith_short_8","alias_value":"CQA6IU5N","created_at":"2026-07-05T05:21:48Z"}],"graph_snapshots":[{"event_id":"sha256:7e7a5d042ab7abecdafd725110afa73cc24e53a6fcba0a841c1ea21f080b1961","target":"graph","created_at":"2026-07-05T05:21:48Z","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/2212.01026/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although augmentations (e.g., perturbation of graph edges, image crops) boost the efficiency of Contrastive Learning (CL), feature level augmentation is another plausible, complementary yet not well researched strategy. Thus, we present a novel spectral feature argumentation for contrastive learning on graphs (and images). To this end, for each data view, we estimate a low-rank approximation per feature map and subtract that approximation from the map to obtain its complement. This is achieved by the proposed herein incomplete power iteration, a non-standard power iteration regime which enjoys","authors_text":"Hao Zhu, Irwin King, Piotr Koniusz, Yifei Zhang, Zixing Song","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-02T08:48:11Z","title":"Spectral Feature Augmentation for Graph Contrastive Learning and Beyond"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.01026","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":"sha256:2e07d1f6b439e7f5b5320591152fa26f8cc7a9f140b7dfdbc23eadd6f88d1d4f","target":"record","created_at":"2026-07-05T05:21:48Z","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":"75a6435d91f027257b1271655b5c10225ddbfd9a82a53108c5862df23392b027","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-02T08:48:11Z","title_canon_sha256":"8605092b9ab88fb0be1b03b986f205f17b06b10c187b2fc19cf9339f3590bcb6"},"schema_version":"1.0","source":{"id":"2212.01026","kind":"arxiv","version":1}},"canonical_sha256":"1401e453adea2f7c0f46536e4a61c2585269934865ef07c94451b69aa4a64169","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1401e453adea2f7c0f46536e4a61c2585269934865ef07c94451b69aa4a64169","first_computed_at":"2026-07-05T05:21:48.722924Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:21:48.722924Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3DmNysXF0GwG2t95sW9xv9VDTfEGs9VgxRh0nHECLtxPU1Gb0YYzKwgQ5ZmSxfaap9cUwDxsI/qN5RjupCpnCw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:21:48.723388Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.01026","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e07d1f6b439e7f5b5320591152fa26f8cc7a9f140b7dfdbc23eadd6f88d1d4f","sha256:7e7a5d042ab7abecdafd725110afa73cc24e53a6fcba0a841c1ea21f080b1961"],"state_sha256":"8f8aa4a6bb57b549320cdf7e159cf1c390192a6316df7b4512437e7bef65e738"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KcleWKtAVrF3phyvPzKKJ4Ux8p/dADQGkKeJRlvuuBQMLgx9tbSLCTjwMOcoyQBdf38aM0zi8jHOSGc3Wx3HBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T06:13:15.467553Z","bundle_sha256":"bcc3d1f16b0ff3ee4b3e06a1d7666b6ff22f1af08bdd31ab3600c8d0c6a52524"}}