{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:GJID2GS2ZSJKDQGV3YSHVC26ID","short_pith_number":"pith:GJID2GS2","canonical_record":{"source":{"id":"1505.02108","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-08T17:39:23Z","cross_cats_sorted":[],"title_canon_sha256":"f79dc8bb7cbf0d3889bd1b0099b750ff5cdbe715831e8fba45e1222bcdb8f3b4","abstract_canon_sha256":"6a31452e6968483b9e08d405775376d87ae8c0ffcd16c42ff9fcf49bd2fa0556"},"schema_version":"1.0"},"canonical_sha256":"32503d1a5acc92a1c0d5de247a8b5e40f80d396127cd52dce1003223f19752c6","source":{"kind":"arxiv","id":"1505.02108","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1505.02108","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"arxiv_version","alias_value":"1505.02108v2","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.02108","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"pith_short_12","alias_value":"GJID2GS2ZSJK","created_at":"2026-05-18T12:29:22Z"},{"alias_kind":"pith_short_16","alias_value":"GJID2GS2ZSJKDQGV","created_at":"2026-05-18T12:29:22Z"},{"alias_kind":"pith_short_8","alias_value":"GJID2GS2","created_at":"2026-05-18T12:29:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:GJID2GS2ZSJKDQGV3YSHVC26ID","target":"record","payload":{"canonical_record":{"source":{"id":"1505.02108","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-08T17:39:23Z","cross_cats_sorted":[],"title_canon_sha256":"f79dc8bb7cbf0d3889bd1b0099b750ff5cdbe715831e8fba45e1222bcdb8f3b4","abstract_canon_sha256":"6a31452e6968483b9e08d405775376d87ae8c0ffcd16c42ff9fcf49bd2fa0556"},"schema_version":"1.0"},"canonical_sha256":"32503d1a5acc92a1c0d5de247a8b5e40f80d396127cd52dce1003223f19752c6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:33:51.609078Z","signature_b64":"ksVfmyzWVmZNULVa2X2CvKKi98U0mhOfqap+n9QPtZsmqOCVqx1Z0EhlkseUt97R87kX692+nPKNqJ+5DfEeDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32503d1a5acc92a1c0d5de247a8b5e40f80d396127cd52dce1003223f19752c6","last_reissued_at":"2026-05-18T01:33:51.608562Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:33:51.608562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1505.02108","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":"2026-05-18T01:33:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GpM7rR4MVvd0fnMPhVqYuiOuOL4ibeWs2IeKHPCDDMFWblSYy58CoUwsED5iCyfAbk2RgSvYx2G4hL10eR3vAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:30:30.155123Z"},"content_sha256":"8d00293f002bceab4d115fad6d48a9a5cf0c8dbe980d57c35ef904b35280abd0","schema_version":"1.0","event_id":"sha256:8d00293f002bceab4d115fad6d48a9a5cf0c8dbe980d57c35ef904b35280abd0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:GJID2GS2ZSJKDQGV3YSHVC26ID","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MegaFace: A Million Faces for Recognition at Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"D. Miller, E. Brossard, I. Kemelmacher-Shlizerman, S. Seitz","submitted_at":"2015-05-08T17:39:23Z","abstract_excerpt":"Recent face recognition experiments on the LFW benchmark show that face recognition is performing stunningly well, surpassing human recognition rates. In this paper, we study face recognition at scale. Specifically, we have collected from Flickr a \\textbf{Million} faces and evaluated state of the art face recognition algorithms on this dataset. We found that the performance of algorithms varies--while all perform great on LFW, once evaluated at scale recognition rates drop drastically for most algorithms. Interestingly, deep learning based approach by \\cite{schroff2015facenet} performs much be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.02108","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":""},"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":"2026-05-18T01:33:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2M9nZK3WxTGhStxZwR3BEmBtyz07ovP0N4eaaPbfK3AnxElld6KTlhTiGUPuvv4U20EOg91sXpz6Je4hG4y4Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:30:30.156719Z"},"content_sha256":"4ca941d80778d90d7c6184b004686e8977f4db167657d36f0c57e021f20e09d8","schema_version":"1.0","event_id":"sha256:4ca941d80778d90d7c6184b004686e8977f4db167657d36f0c57e021f20e09d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/bundle.json","state_url":"https://pith.science/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/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":"2026-06-04T23:30:30Z","links":{"resolver":"https://pith.science/pith/GJID2GS2ZSJKDQGV3YSHVC26ID","bundle":"https://pith.science/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/bundle.json","state":"https://pith.science/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GJID2GS2ZSJKDQGV3YSHVC26ID/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:GJID2GS2ZSJKDQGV3YSHVC26ID","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":"6a31452e6968483b9e08d405775376d87ae8c0ffcd16c42ff9fcf49bd2fa0556","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-08T17:39:23Z","title_canon_sha256":"f79dc8bb7cbf0d3889bd1b0099b750ff5cdbe715831e8fba45e1222bcdb8f3b4"},"schema_version":"1.0","source":{"id":"1505.02108","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1505.02108","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"arxiv_version","alias_value":"1505.02108v2","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.02108","created_at":"2026-05-18T01:33:51Z"},{"alias_kind":"pith_short_12","alias_value":"GJID2GS2ZSJK","created_at":"2026-05-18T12:29:22Z"},{"alias_kind":"pith_short_16","alias_value":"GJID2GS2ZSJKDQGV","created_at":"2026-05-18T12:29:22Z"},{"alias_kind":"pith_short_8","alias_value":"GJID2GS2","created_at":"2026-05-18T12:29:22Z"}],"graph_snapshots":[{"event_id":"sha256:4ca941d80778d90d7c6184b004686e8977f4db167657d36f0c57e021f20e09d8","target":"graph","created_at":"2026-05-18T01:33:51Z","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"},"paper":{"abstract_excerpt":"Recent face recognition experiments on the LFW benchmark show that face recognition is performing stunningly well, surpassing human recognition rates. In this paper, we study face recognition at scale. Specifically, we have collected from Flickr a \\textbf{Million} faces and evaluated state of the art face recognition algorithms on this dataset. We found that the performance of algorithms varies--while all perform great on LFW, once evaluated at scale recognition rates drop drastically for most algorithms. Interestingly, deep learning based approach by \\cite{schroff2015facenet} performs much be","authors_text":"D. Miller, E. Brossard, I. Kemelmacher-Shlizerman, S. Seitz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-08T17:39:23Z","title":"MegaFace: A Million Faces for Recognition at Scale"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.02108","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":"sha256:8d00293f002bceab4d115fad6d48a9a5cf0c8dbe980d57c35ef904b35280abd0","target":"record","created_at":"2026-05-18T01:33:51Z","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":"6a31452e6968483b9e08d405775376d87ae8c0ffcd16c42ff9fcf49bd2fa0556","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-08T17:39:23Z","title_canon_sha256":"f79dc8bb7cbf0d3889bd1b0099b750ff5cdbe715831e8fba45e1222bcdb8f3b4"},"schema_version":"1.0","source":{"id":"1505.02108","kind":"arxiv","version":2}},"canonical_sha256":"32503d1a5acc92a1c0d5de247a8b5e40f80d396127cd52dce1003223f19752c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"32503d1a5acc92a1c0d5de247a8b5e40f80d396127cd52dce1003223f19752c6","first_computed_at":"2026-05-18T01:33:51.608562Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:33:51.608562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ksVfmyzWVmZNULVa2X2CvKKi98U0mhOfqap+n9QPtZsmqOCVqx1Z0EhlkseUt97R87kX692+nPKNqJ+5DfEeDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:33:51.609078Z","signed_message":"canonical_sha256_bytes"},"source_id":"1505.02108","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d00293f002bceab4d115fad6d48a9a5cf0c8dbe980d57c35ef904b35280abd0","sha256:4ca941d80778d90d7c6184b004686e8977f4db167657d36f0c57e021f20e09d8"],"state_sha256":"b2fa81b42b97106123cc711f72e9d1b055ffb9fde846bd395a1a7e7a34f09ad0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iS17giPKUg/Kyn9e948x48EbInefh34CC6D6nLTYw1vKS12pAwmoCG+vgkmRtB7Q60kWcKxEQvlluM1NTTNgBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T23:30:30.160347Z","bundle_sha256":"de1add0b9f9fe0b5aac9f608a40f3dded078695354196942eea9d0c7723e5274"}}