{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:VOUYRAJZE7IACBT4YS5P5BZ36H","short_pith_number":"pith:VOUYRAJZ","canonical_record":{"source":{"id":"2106.04619","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-06-08T18:18:09Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"7b65ec1d2c3f14f65a8fea8f056e76f9db89ffe3d0ea0bd9c091f708a11be5e0","abstract_canon_sha256":"efc72f1354486a70a5c47e1108c6ab3ed9e87a39cdbd2e9fce683d04522db8d3"},"schema_version":"1.0"},"canonical_sha256":"aba988813927d001067cc4bafe873bf1c8df377e7cfed42de1d43c9b97c32e88","source":{"kind":"arxiv","id":"2106.04619","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04619","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04619v4","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04619","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_12","alias_value":"VOUYRAJZE7IA","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_16","alias_value":"VOUYRAJZE7IACBT4","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_8","alias_value":"VOUYRAJZ","created_at":"2026-07-05T03:48:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:VOUYRAJZE7IACBT4YS5P5BZ36H","target":"record","payload":{"canonical_record":{"source":{"id":"2106.04619","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-06-08T18:18:09Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"7b65ec1d2c3f14f65a8fea8f056e76f9db89ffe3d0ea0bd9c091f708a11be5e0","abstract_canon_sha256":"efc72f1354486a70a5c47e1108c6ab3ed9e87a39cdbd2e9fce683d04522db8d3"},"schema_version":"1.0"},"canonical_sha256":"aba988813927d001067cc4bafe873bf1c8df377e7cfed42de1d43c9b97c32e88","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:48:29.622819Z","signature_b64":"OIk2lreBu+ANo61weMO37ktFuxWqyIW2KIYSxo441dYJAAtWYAWPfe6ZNGdQE0m6HmOEOCTuDWzULGBeo/S2Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aba988813927d001067cc4bafe873bf1c8df377e7cfed42de1d43c9b97c32e88","last_reissued_at":"2026-07-05T03:48:29.622370Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:48:29.622370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.04619","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:48:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tqx3OHFu95VBsAr9bKLKskhgnZQ4o1QMhm+uJNAKX5DmhXgTOOii5sM3HXMu9758gPjZSnROrAw/1aO8/HCRDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:10:54.412571Z"},"content_sha256":"643cf92b48792db90327c8112580e3a7356a552fec0ea44cda7a58cdd81f2889","schema_version":"1.0","event_id":"sha256:643cf92b48792db90327c8112580e3a7356a552fec0ea44cda7a58cdd81f2889"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:VOUYRAJZE7IACBT4YS5P5BZ36H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Bernhard Sch\\\"olkopf, Francesco Locatello, Julius von K\\\"ugelgen, Luigi Gresele, Michel Besserve, Wieland Brendel, Yash Sharma","submitted_at":"2021-06-08T18:18:09Z","abstract_excerpt":"Self-supervised representation learning has shown remarkable success in a number of domains. A common practice is to perform data augmentation via hand-crafted transformations intended to leave the semantics of the data invariant. We seek to understand the empirical success of this approach from a theoretical perspective. We formulate the augmentation process as a latent variable model by postulating a partition of the latent representation into a content component, which is assumed invariant to augmentation, and a style component, which is allowed to change. Unlike prior work on disentangleme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04619","kind":"arxiv","version":4},"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/2106.04619/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":"2026-07-05T03:48:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+hDn5JnAjarGPv0HRMDYLOvTdBmpiECZSSlhNDlXL78o8Ym3hER4U0WSGCz6a4ZpMa3U0xzVSHo3dGj0k7uVAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:10:54.412982Z"},"content_sha256":"981c70f91d6967223b41bd1d0b8024c858bfda92c502679a580ce2d894621b7e","schema_version":"1.0","event_id":"sha256:981c70f91d6967223b41bd1d0b8024c858bfda92c502679a580ce2d894621b7e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/bundle.json","state_url":"https://pith.science/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/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":"2026-08-06T09:10:54Z","links":{"resolver":"https://pith.science/pith/VOUYRAJZE7IACBT4YS5P5BZ36H","bundle":"https://pith.science/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/bundle.json","state":"https://pith.science/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VOUYRAJZE7IACBT4YS5P5BZ36H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:VOUYRAJZE7IACBT4YS5P5BZ36H","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":"efc72f1354486a70a5c47e1108c6ab3ed9e87a39cdbd2e9fce683d04522db8d3","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-06-08T18:18:09Z","title_canon_sha256":"7b65ec1d2c3f14f65a8fea8f056e76f9db89ffe3d0ea0bd9c091f708a11be5e0"},"schema_version":"1.0","source":{"id":"2106.04619","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04619","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04619v4","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04619","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_12","alias_value":"VOUYRAJZE7IA","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_16","alias_value":"VOUYRAJZE7IACBT4","created_at":"2026-07-05T03:48:29Z"},{"alias_kind":"pith_short_8","alias_value":"VOUYRAJZ","created_at":"2026-07-05T03:48:29Z"}],"graph_snapshots":[{"event_id":"sha256:981c70f91d6967223b41bd1d0b8024c858bfda92c502679a580ce2d894621b7e","target":"graph","created_at":"2026-07-05T03:48:29Z","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/2106.04619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Self-supervised representation learning has shown remarkable success in a number of domains. A common practice is to perform data augmentation via hand-crafted transformations intended to leave the semantics of the data invariant. We seek to understand the empirical success of this approach from a theoretical perspective. We formulate the augmentation process as a latent variable model by postulating a partition of the latent representation into a content component, which is assumed invariant to augmentation, and a style component, which is allowed to change. Unlike prior work on disentangleme","authors_text":"Bernhard Sch\\\"olkopf, Francesco Locatello, Julius von K\\\"ugelgen, Luigi Gresele, Michel Besserve, Wieland Brendel, Yash Sharma","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-06-08T18:18:09Z","title":"Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04619","kind":"arxiv","version":4},"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":"sha256:643cf92b48792db90327c8112580e3a7356a552fec0ea44cda7a58cdd81f2889","target":"record","created_at":"2026-07-05T03:48:29Z","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":"efc72f1354486a70a5c47e1108c6ab3ed9e87a39cdbd2e9fce683d04522db8d3","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-06-08T18:18:09Z","title_canon_sha256":"7b65ec1d2c3f14f65a8fea8f056e76f9db89ffe3d0ea0bd9c091f708a11be5e0"},"schema_version":"1.0","source":{"id":"2106.04619","kind":"arxiv","version":4}},"canonical_sha256":"aba988813927d001067cc4bafe873bf1c8df377e7cfed42de1d43c9b97c32e88","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aba988813927d001067cc4bafe873bf1c8df377e7cfed42de1d43c9b97c32e88","first_computed_at":"2026-07-05T03:48:29.622370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:48:29.622370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OIk2lreBu+ANo61weMO37ktFuxWqyIW2KIYSxo441dYJAAtWYAWPfe6ZNGdQE0m6HmOEOCTuDWzULGBeo/S2Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:48:29.622819Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.04619","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:643cf92b48792db90327c8112580e3a7356a552fec0ea44cda7a58cdd81f2889","sha256:981c70f91d6967223b41bd1d0b8024c858bfda92c502679a580ce2d894621b7e"],"state_sha256":"7e9b42d7665dd43e0f6d9865616869583b3a849bced26283054b6ab2d408402d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xJKaOifw3gjLexpz+Bshs3b65AVmZ3baPwVDG0HS/rCDfSO8uXNNP7gM+DC3129uvX4ITn+d1G2To3IxtFC2CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T09:10:54.417372Z","bundle_sha256":"ff381498544e3fa52d289ccf0faf62542d8bffc983610d0ed2b4b005d9131e77"}}