{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:24XSV37Z43FLZUHNOEOC24ELD7","short_pith_number":"pith:24XSV37Z","canonical_record":{"source":{"id":"2004.00445","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T13:39:37Z","cross_cats_sorted":[],"title_canon_sha256":"1757776770d71b5a0da4e099f4cbea7d698203058926c98b9bfcc382a6e3f740","abstract_canon_sha256":"b02c1427e2e0dd95759f637bb56785b74885e5d3a40b5fcb608c3683f85d3390"},"schema_version":"1.0"},"canonical_sha256":"d72f2aeff9e6cabcd0ed711c2d708b1fc8194267902f197a6f09cc3b59ee4aea","source":{"kind":"arxiv","id":"2004.00445","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00445","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00445v2","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00445","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_12","alias_value":"24XSV37Z43FL","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_16","alias_value":"24XSV37Z43FLZUHN","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_8","alias_value":"24XSV37Z","created_at":"2026-07-05T00:52:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:24XSV37Z43FLZUHNOEOC24ELD7","target":"record","payload":{"canonical_record":{"source":{"id":"2004.00445","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T13:39:37Z","cross_cats_sorted":[],"title_canon_sha256":"1757776770d71b5a0da4e099f4cbea7d698203058926c98b9bfcc382a6e3f740","abstract_canon_sha256":"b02c1427e2e0dd95759f637bb56785b74885e5d3a40b5fcb608c3683f85d3390"},"schema_version":"1.0"},"canonical_sha256":"d72f2aeff9e6cabcd0ed711c2d708b1fc8194267902f197a6f09cc3b59ee4aea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:52:30.810238Z","signature_b64":"uwCkwBwyncr2L34wLUJ4OXHxfOvhTsfU7szIbfQYEjtxI9D8/i9xe81IXTYHuaZ7KoJ1oICL5Kmf4LXsYy0tBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d72f2aeff9e6cabcd0ed711c2d708b1fc8194267902f197a6f09cc3b59ee4aea","last_reissued_at":"2026-07-05T00:52:30.809795Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:52:30.809795Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.00445","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":"2026-07-05T00:52:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oXn6dI+I1KIFhXvvJvyqIBwDKcaqh3BOpILKW0PdKrl7P34dIVEPyk7wlAY9CuyTdr9vditAYibgpvlERhbhBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:24:27.112169Z"},"content_sha256":"205a9158096db939db3e029e986e193ac05ed28990772b97923d2033fb0cc618","schema_version":"1.0","event_id":"sha256:205a9158096db939db3e029e986e193ac05ed28990772b97923d2033fb0cc618"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:24XSV37Z43FLZUHNOEOC24ELD7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Cluster Faces via Confidence and Connectivity Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Change Loy, Dahua Lin, Dapeng Chen, Lei Yang, Rui Zhao, Xiaohang Zhan","submitted_at":"2020-04-01T13:39:37Z","abstract_excerpt":"Face clustering is an essential tool for exploiting the unlabeled face data, and has a wide range of applications including face annotation and retrieval. Recent works show that supervised clustering can result in noticeable performance gain. However, they usually involve heuristic steps and require numerous overlapped subgraphs, severely restricting their accuracy and efficiency. In this paper, we propose a fully learnable clustering framework without requiring a large number of overlapped subgraphs. Instead, we transform the clustering problem into two sub-problems. Specifically, two graph c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00445","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/2004.00445/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":"2026-07-05T00:52:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"//TNsjBZgP73GDSJ15DaBA5aM+tGLsjgX2tWae68r4evwsKbky5aBKEpOEkcu4IuQckwJ6NPM4TK4+k8x1sNAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:24:27.112664Z"},"content_sha256":"ca4bf1a2b6adcffa18817a0fd09c657dfc9840376117242bc940c5b600873b0c","schema_version":"1.0","event_id":"sha256:ca4bf1a2b6adcffa18817a0fd09c657dfc9840376117242bc940c5b600873b0c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/24XSV37Z43FLZUHNOEOC24ELD7/bundle.json","state_url":"https://pith.science/pith/24XSV37Z43FLZUHNOEOC24ELD7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/24XSV37Z43FLZUHNOEOC24ELD7/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":"2026-08-21T05:24:27Z","links":{"resolver":"https://pith.science/pith/24XSV37Z43FLZUHNOEOC24ELD7","bundle":"https://pith.science/pith/24XSV37Z43FLZUHNOEOC24ELD7/bundle.json","state":"https://pith.science/pith/24XSV37Z43FLZUHNOEOC24ELD7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/24XSV37Z43FLZUHNOEOC24ELD7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:24XSV37Z43FLZUHNOEOC24ELD7","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":"b02c1427e2e0dd95759f637bb56785b74885e5d3a40b5fcb608c3683f85d3390","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T13:39:37Z","title_canon_sha256":"1757776770d71b5a0da4e099f4cbea7d698203058926c98b9bfcc382a6e3f740"},"schema_version":"1.0","source":{"id":"2004.00445","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00445","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00445v2","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00445","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_12","alias_value":"24XSV37Z43FL","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_16","alias_value":"24XSV37Z43FLZUHN","created_at":"2026-07-05T00:52:30Z"},{"alias_kind":"pith_short_8","alias_value":"24XSV37Z","created_at":"2026-07-05T00:52:30Z"}],"graph_snapshots":[{"event_id":"sha256:ca4bf1a2b6adcffa18817a0fd09c657dfc9840376117242bc940c5b600873b0c","target":"graph","created_at":"2026-07-05T00:52:30Z","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/2004.00445/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Face clustering is an essential tool for exploiting the unlabeled face data, and has a wide range of applications including face annotation and retrieval. Recent works show that supervised clustering can result in noticeable performance gain. However, they usually involve heuristic steps and require numerous overlapped subgraphs, severely restricting their accuracy and efficiency. In this paper, we propose a fully learnable clustering framework without requiring a large number of overlapped subgraphs. Instead, we transform the clustering problem into two sub-problems. Specifically, two graph c","authors_text":"Chen Change Loy, Dahua Lin, Dapeng Chen, Lei Yang, Rui Zhao, Xiaohang Zhan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T13:39:37Z","title":"Learning to Cluster Faces via Confidence and Connectivity Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00445","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":"sha256:205a9158096db939db3e029e986e193ac05ed28990772b97923d2033fb0cc618","target":"record","created_at":"2026-07-05T00:52:30Z","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":"b02c1427e2e0dd95759f637bb56785b74885e5d3a40b5fcb608c3683f85d3390","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T13:39:37Z","title_canon_sha256":"1757776770d71b5a0da4e099f4cbea7d698203058926c98b9bfcc382a6e3f740"},"schema_version":"1.0","source":{"id":"2004.00445","kind":"arxiv","version":2}},"canonical_sha256":"d72f2aeff9e6cabcd0ed711c2d708b1fc8194267902f197a6f09cc3b59ee4aea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d72f2aeff9e6cabcd0ed711c2d708b1fc8194267902f197a6f09cc3b59ee4aea","first_computed_at":"2026-07-05T00:52:30.809795Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:52:30.809795Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uwCkwBwyncr2L34wLUJ4OXHxfOvhTsfU7szIbfQYEjtxI9D8/i9xe81IXTYHuaZ7KoJ1oICL5Kmf4LXsYy0tBw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:52:30.810238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.00445","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:205a9158096db939db3e029e986e193ac05ed28990772b97923d2033fb0cc618","sha256:ca4bf1a2b6adcffa18817a0fd09c657dfc9840376117242bc940c5b600873b0c"],"state_sha256":"ee35ed3ad380c707958a164fadff33ce9ec3310520bc45053952a4745c45ff02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iu//wP8/WFB6Nipekl9wmau4RYfChtzD2kZSi0PWqoVBjwJX45k2i5YfnDofNMpm22OVBDF3I0f5xzDfRtrGCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T05:24:27.116174Z","bundle_sha256":"833cda8a4b13ce6d95b121cedf2fdffd5a75397038f6cf8214518acc7a1f1065"}}