{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:GW4QE4IZP5NLN5JYN36N6THOZD","short_pith_number":"pith:GW4QE4IZ","canonical_record":{"source":{"id":"2104.03602","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-08T08:34:04Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0ded9256c055196f060b354da9af96bb1fc29772f4752dd8501011629af886a7","abstract_canon_sha256":"15a7c2f84caf12d759b409756a99ad66a26073256209ebe74f1b38a536b5c625"},"schema_version":"1.0"},"canonical_sha256":"35b90271197f5ab6f5386efcdf4ceec8e702c534ef7678b6176ae8ef7a3d39c5","source":{"kind":"arxiv","id":"2104.03602","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.03602","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"arxiv_version","alias_value":"2104.03602v3","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.03602","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_12","alias_value":"GW4QE4IZP5NL","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"GW4QE4IZP5NLN5JY","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"GW4QE4IZ","created_at":"2026-07-05T05:28:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:GW4QE4IZP5NLN5JYN36N6THOZD","target":"record","payload":{"canonical_record":{"source":{"id":"2104.03602","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-08T08:34:04Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0ded9256c055196f060b354da9af96bb1fc29772f4752dd8501011629af886a7","abstract_canon_sha256":"15a7c2f84caf12d759b409756a99ad66a26073256209ebe74f1b38a536b5c625"},"schema_version":"1.0"},"canonical_sha256":"35b90271197f5ab6f5386efcdf4ceec8e702c534ef7678b6176ae8ef7a3d39c5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:28:41.698524Z","signature_b64":"L8YZhRnxPM8c/K28FqA4Zj51a1zA2IRutYo/f5E2/AmzrXIz6mSyj95kuB/Rm3lDdN4Jwru0JMNwzIxUWFj5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35b90271197f5ab6f5386efcdf4ceec8e702c534ef7678b6176ae8ef7a3d39c5","last_reissued_at":"2026-07-05T05:28:41.698104Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:28:41.698104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.03602","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":"2026-07-05T05:28:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"06CQbuLSMoofG0j3sDPTFV0Mjw84npiZYYTHMuqNoe6BNjUMMV2/WuJ4rD4G+Fr2dMqZaZVchVgQM0PZ9FzEDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:31:54.785637Z"},"content_sha256":"b4bd1b521d767ba9b1f509ee0ee979f43390e5aa4dab20925ee0ebec7d9c38cc","schema_version":"1.0","event_id":"sha256:b4bd1b521d767ba9b1f509ee0ee979f43390e5aa4dab20925ee0ebec7d9c38cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:GW4QE4IZP5NLN5JYN36N6THOZD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SiT: Self-supervised vIsion Transformer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Josef Kittler, Muhammad Awais, Sara Atito","submitted_at":"2021-04-08T08:34:04Z","abstract_excerpt":"Self-supervised learning methods are gaining increasing traction in computer vision due to their recent success in reducing the gap with supervised learning. In natural language processing (NLP) self-supervised learning and transformers are already the methods of choice. The recent literature suggests that the transformers are becoming increasingly popular also in computer vision. So far, the vision transformers have been shown to work well when pretrained either using a large scale supervised data or with some kind of co-supervision, e.g. in terms of teacher network. These supervised pretrain"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.03602","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/2104.03602/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":"2026-07-05T05:28:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c4U+//cB7F2NMmSRUgRjXCcfLDSbmBUSXt8XBz8Hb1CogRVuU3tmxJRUn5g+qZDkWvBIUNm1B5Ux8f9VJ87LCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:31:54.786568Z"},"content_sha256":"bafedce5e9574a0dab263f05dd8915ea78314b6572abc08569c11f815a52f41e","schema_version":"1.0","event_id":"sha256:bafedce5e9574a0dab263f05dd8915ea78314b6572abc08569c11f815a52f41e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GW4QE4IZP5NLN5JYN36N6THOZD/bundle.json","state_url":"https://pith.science/pith/GW4QE4IZP5NLN5JYN36N6THOZD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GW4QE4IZP5NLN5JYN36N6THOZD/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":"2026-08-10T11:31:54Z","links":{"resolver":"https://pith.science/pith/GW4QE4IZP5NLN5JYN36N6THOZD","bundle":"https://pith.science/pith/GW4QE4IZP5NLN5JYN36N6THOZD/bundle.json","state":"https://pith.science/pith/GW4QE4IZP5NLN5JYN36N6THOZD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GW4QE4IZP5NLN5JYN36N6THOZD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:GW4QE4IZP5NLN5JYN36N6THOZD","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":"15a7c2f84caf12d759b409756a99ad66a26073256209ebe74f1b38a536b5c625","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-08T08:34:04Z","title_canon_sha256":"0ded9256c055196f060b354da9af96bb1fc29772f4752dd8501011629af886a7"},"schema_version":"1.0","source":{"id":"2104.03602","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.03602","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"arxiv_version","alias_value":"2104.03602v3","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.03602","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_12","alias_value":"GW4QE4IZP5NL","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"GW4QE4IZP5NLN5JY","created_at":"2026-07-05T05:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"GW4QE4IZ","created_at":"2026-07-05T05:28:41Z"}],"graph_snapshots":[{"event_id":"sha256:bafedce5e9574a0dab263f05dd8915ea78314b6572abc08569c11f815a52f41e","target":"graph","created_at":"2026-07-05T05:28:41Z","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/2104.03602/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Self-supervised learning methods are gaining increasing traction in computer vision due to their recent success in reducing the gap with supervised learning. In natural language processing (NLP) self-supervised learning and transformers are already the methods of choice. The recent literature suggests that the transformers are becoming increasingly popular also in computer vision. So far, the vision transformers have been shown to work well when pretrained either using a large scale supervised data or with some kind of co-supervision, e.g. in terms of teacher network. These supervised pretrain","authors_text":"Josef Kittler, Muhammad Awais, Sara Atito","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-08T08:34:04Z","title":"SiT: Self-supervised vIsion Transformer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.03602","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:b4bd1b521d767ba9b1f509ee0ee979f43390e5aa4dab20925ee0ebec7d9c38cc","target":"record","created_at":"2026-07-05T05:28:41Z","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":"15a7c2f84caf12d759b409756a99ad66a26073256209ebe74f1b38a536b5c625","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-08T08:34:04Z","title_canon_sha256":"0ded9256c055196f060b354da9af96bb1fc29772f4752dd8501011629af886a7"},"schema_version":"1.0","source":{"id":"2104.03602","kind":"arxiv","version":3}},"canonical_sha256":"35b90271197f5ab6f5386efcdf4ceec8e702c534ef7678b6176ae8ef7a3d39c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35b90271197f5ab6f5386efcdf4ceec8e702c534ef7678b6176ae8ef7a3d39c5","first_computed_at":"2026-07-05T05:28:41.698104Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:28:41.698104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L8YZhRnxPM8c/K28FqA4Zj51a1zA2IRutYo/f5E2/AmzrXIz6mSyj95kuB/Rm3lDdN4Jwru0JMNwzIxUWFj5DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:28:41.698524Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.03602","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4bd1b521d767ba9b1f509ee0ee979f43390e5aa4dab20925ee0ebec7d9c38cc","sha256:bafedce5e9574a0dab263f05dd8915ea78314b6572abc08569c11f815a52f41e"],"state_sha256":"4b512569491f5438a7fb42915e56143430fa2bece02eeb8deee2406371528715"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kDho1Sm39QdUXJE6GeOjrgesbKPtBbNgamG6H1fIGGYRndGe8EN45KoFe8r79IVlnzHx0BSLnqay3Pr/3BYNCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T11:31:54.792789Z","bundle_sha256":"59692a0bc9f0e8257932358e3d6b24d49a5edd536cdea6d1da0e5b07c6ef8671"}}