{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6JPBCBLOMBEVARECDBC3PRTJSA","short_pith_number":"pith:6JPBCBLO","canonical_record":{"source":{"id":"2001.07685","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-21T18:32:27Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"95d775d555de3700bee85240d7470369cdb1543a12b5746d396fedf2cd5fa343","abstract_canon_sha256":"4acea3e681534680a1ef68c28a304e64fd3af97f4060d444f98f30e53d52230d"},"schema_version":"1.0"},"canonical_sha256":"f25e11056e60495044821845b7c6699017609d9f8d41fb4848999e27f83836ee","source":{"kind":"arxiv","id":"2001.07685","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.07685","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"2001.07685v2","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.07685","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"6JPBCBLOMBEV","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_16","alias_value":"6JPBCBLOMBEVAREC","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_8","alias_value":"6JPBCBLO","created_at":"2026-07-05T01:54:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6JPBCBLOMBEVARECDBC3PRTJSA","target":"record","payload":{"canonical_record":{"source":{"id":"2001.07685","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-21T18:32:27Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"95d775d555de3700bee85240d7470369cdb1543a12b5746d396fedf2cd5fa343","abstract_canon_sha256":"4acea3e681534680a1ef68c28a304e64fd3af97f4060d444f98f30e53d52230d"},"schema_version":"1.0"},"canonical_sha256":"f25e11056e60495044821845b7c6699017609d9f8d41fb4848999e27f83836ee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:54:27.354388Z","signature_b64":"PSYC2Jp5j79SnUqQo5vwhhINV2sTpotzLqlyAz3w1BRhLoZG+D9CMI6tjgmY1unzEoICKJl80qNVUY5B6xhrDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f25e11056e60495044821845b7c6699017609d9f8d41fb4848999e27f83836ee","last_reissued_at":"2026-07-05T01:54:27.353843Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:54:27.353843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2001.07685","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":"2026-07-05T01:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"srLmSApL3hvr35DjnekwnH7eA9MgXbdW5RfCkPa6xhVhi4nAwKqqAfrDhF+t/MJBknoI/N9hE75zuvRlvacWAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:49:14.779061Z"},"content_sha256":"9d227fff1f6fd053bfb2fa6b95682e15a4aab3690c6a9091d845664aad9d0632","schema_version":"1.0","event_id":"sha256:9d227fff1f6fd053bfb2fa6b95682e15a4aab3690c6a9091d845664aad9d0632"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6JPBCBLOMBEVARECDBC3PRTJSA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alex Kurakin, Chun-Liang Li, Colin Raffel, David Berthelot, Ekin D. Cubuk, Han Zhang, Kihyuk Sohn, Nicholas Carlini, Zizhao Zhang","submitted_at":"2020-01-21T18:32:27Z","abstract_excerpt":"Semi-supervised learning (SSL) provides an effective means of leveraging unlabeled data to improve a model's performance. In this paper, we demonstrate the power of a simple combination of two common SSL methods: consistency regularization and pseudo-labeling. Our algorithm, FixMatch, first generates pseudo-labels using the model's predictions on weakly-augmented unlabeled images. For a given image, the pseudo-label is only retained if the model produces a high-confidence prediction. The model is then trained to predict the pseudo-label when fed a strongly-augmented version of the same image. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.07685","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/2001.07685/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":"2026-07-05T01:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2ZEZZXFRAgO2QMvsVp6bawjP/olCQX36PZJMIhxlXDb0/Oygeh9iphV9ZbePyaqxqtpP0zXyn+KSDKJ2RdMlCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:49:14.779755Z"},"content_sha256":"5f086a0c51a2335acc79f0f138ada5971ebb879f2deebc91ba5d47160dd29d31","schema_version":"1.0","event_id":"sha256:5f086a0c51a2335acc79f0f138ada5971ebb879f2deebc91ba5d47160dd29d31"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6JPBCBLOMBEVARECDBC3PRTJSA/bundle.json","state_url":"https://pith.science/pith/6JPBCBLOMBEVARECDBC3PRTJSA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6JPBCBLOMBEVARECDBC3PRTJSA/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":"2026-07-11T02:49:14Z","links":{"resolver":"https://pith.science/pith/6JPBCBLOMBEVARECDBC3PRTJSA","bundle":"https://pith.science/pith/6JPBCBLOMBEVARECDBC3PRTJSA/bundle.json","state":"https://pith.science/pith/6JPBCBLOMBEVARECDBC3PRTJSA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6JPBCBLOMBEVARECDBC3PRTJSA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6JPBCBLOMBEVARECDBC3PRTJSA","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":"4acea3e681534680a1ef68c28a304e64fd3af97f4060d444f98f30e53d52230d","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-21T18:32:27Z","title_canon_sha256":"95d775d555de3700bee85240d7470369cdb1543a12b5746d396fedf2cd5fa343"},"schema_version":"1.0","source":{"id":"2001.07685","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.07685","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"2001.07685v2","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.07685","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"6JPBCBLOMBEV","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_16","alias_value":"6JPBCBLOMBEVAREC","created_at":"2026-07-05T01:54:27Z"},{"alias_kind":"pith_short_8","alias_value":"6JPBCBLO","created_at":"2026-07-05T01:54:27Z"}],"graph_snapshots":[{"event_id":"sha256:5f086a0c51a2335acc79f0f138ada5971ebb879f2deebc91ba5d47160dd29d31","target":"graph","created_at":"2026-07-05T01:54:27Z","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/2001.07685/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semi-supervised learning (SSL) provides an effective means of leveraging unlabeled data to improve a model's performance. In this paper, we demonstrate the power of a simple combination of two common SSL methods: consistency regularization and pseudo-labeling. Our algorithm, FixMatch, first generates pseudo-labels using the model's predictions on weakly-augmented unlabeled images. For a given image, the pseudo-label is only retained if the model produces a high-confidence prediction. The model is then trained to predict the pseudo-label when fed a strongly-augmented version of the same image. ","authors_text":"Alex Kurakin, Chun-Liang Li, Colin Raffel, David Berthelot, Ekin D. Cubuk, Han Zhang, Kihyuk Sohn, Nicholas Carlini, Zizhao Zhang","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-21T18:32:27Z","title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.07685","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":"sha256:9d227fff1f6fd053bfb2fa6b95682e15a4aab3690c6a9091d845664aad9d0632","target":"record","created_at":"2026-07-05T01:54:27Z","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":"4acea3e681534680a1ef68c28a304e64fd3af97f4060d444f98f30e53d52230d","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-21T18:32:27Z","title_canon_sha256":"95d775d555de3700bee85240d7470369cdb1543a12b5746d396fedf2cd5fa343"},"schema_version":"1.0","source":{"id":"2001.07685","kind":"arxiv","version":2}},"canonical_sha256":"f25e11056e60495044821845b7c6699017609d9f8d41fb4848999e27f83836ee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f25e11056e60495044821845b7c6699017609d9f8d41fb4848999e27f83836ee","first_computed_at":"2026-07-05T01:54:27.353843Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:54:27.353843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PSYC2Jp5j79SnUqQo5vwhhINV2sTpotzLqlyAz3w1BRhLoZG+D9CMI6tjgmY1unzEoICKJl80qNVUY5B6xhrDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:54:27.354388Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.07685","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d227fff1f6fd053bfb2fa6b95682e15a4aab3690c6a9091d845664aad9d0632","sha256:5f086a0c51a2335acc79f0f138ada5971ebb879f2deebc91ba5d47160dd29d31"],"state_sha256":"7a6f12cc9d039de0349564b025027dc53bc76c043537cbab30e9495c2cff4d52"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tBSfTDxZHpSIERhuapK14BRathrGffP4WzxL4294nbYLdP5ogxAvYN21qBrvuZeVXJg56WRMaNCqhskCj3f/Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T02:49:14.784599Z","bundle_sha256":"267a9db0500767a3e5f1614d92c8fcbee3a117fff3d97b7c8c53b0a0b43020ac"}}