{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:6NWXL5ABXLA6J5LAQYHRF3UBME","short_pith_number":"pith:6NWXL5AB","canonical_record":{"source":{"id":"2505.19920","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-26T12:45:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5c21439690a34fe59a8ff03441c70c950fffa2678f3dc207833331dc7a102912","abstract_canon_sha256":"a7bb066ae44b2ef78e8040c7c794df519b14fadb8199123537e67842d24f79d6"},"schema_version":"1.0"},"canonical_sha256":"f36d75f401bac1e4f560860f12ee81611809472944f613655c5a131f17c2ff16","source":{"kind":"arxiv","id":"2505.19920","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19920","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19920v1","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19920","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_12","alias_value":"6NWXL5ABXLA6","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_16","alias_value":"6NWXL5ABXLA6J5LA","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_8","alias_value":"6NWXL5AB","created_at":"2026-07-05T11:09:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:6NWXL5ABXLA6J5LAQYHRF3UBME","target":"record","payload":{"canonical_record":{"source":{"id":"2505.19920","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-26T12:45:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5c21439690a34fe59a8ff03441c70c950fffa2678f3dc207833331dc7a102912","abstract_canon_sha256":"a7bb066ae44b2ef78e8040c7c794df519b14fadb8199123537e67842d24f79d6"},"schema_version":"1.0"},"canonical_sha256":"f36d75f401bac1e4f560860f12ee81611809472944f613655c5a131f17c2ff16","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:49.901211Z","signature_b64":"1287hpn2hMd0SDuW1+VFcsTO3ICFB0AdrWg9xaC3agrU+pZ+DwMkcEC/tIpGOZS8hhH/bvyvjyuO/vVsurkxBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f36d75f401bac1e4f560860f12ee81611809472944f613655c5a131f17c2ff16","last_reissued_at":"2026-07-05T11:09:49.900724Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:49.900724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.19920","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:09:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X3HKBELlBpZgztQKdFBFya41Wdzql2AGi+4kxn50KUVpwgndIxOvCQixvyA/lJ9dgpe3n3pIvbbJGvg4Il/OBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:30:42.128636Z"},"content_sha256":"a3db0ec1456944600bba9da7f560c3d8197234b02c7ee744cc6420fb7662462c","schema_version":"1.0","event_id":"sha256:a3db0ec1456944600bba9da7f560c3d8197234b02c7ee744cc6420fb7662462c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:6NWXL5ABXLA6J5LAQYHRF3UBME","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Philipp Terh\\\"orst, Sebastian Gro{\\ss}, Stefan Heindorf","submitted_at":"2025-05-26T12:45:01Z","abstract_excerpt":"Traditional face recognition systems rely on extracting fixed face representations, known as templates, to store and verify identities. These representations are typically generated by neural networks that often lack explainability and raise concerns regarding fairness and privacy. In this work, we propose a novel model-template (MOTE) approach that replaces vector-based face templates with small personalized neural networks. This design enables more responsible face recognition for small and medium-scale systems. During enrollment, MOTE creates a dedicated binary classifier for each identity,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19920","kind":"arxiv","version":1},"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/2505.19920/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":"2026-07-05T11:09:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ybhcoGEi25aJWwAXI6f+fCvMSgg19QHUeyle2qzoPcXTnIehI1GQmyNO0+dPJV+sab6Gru/2UPQ1AvVR2h6MCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:30:42.129161Z"},"content_sha256":"06fc3d842457da76213c4767d36833740cda133414962eb7220278123d7920a9","schema_version":"1.0","event_id":"sha256:06fc3d842457da76213c4767d36833740cda133414962eb7220278123d7920a9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/bundle.json","state_url":"https://pith.science/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/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":"2026-08-10T06:30:42Z","links":{"resolver":"https://pith.science/pith/6NWXL5ABXLA6J5LAQYHRF3UBME","bundle":"https://pith.science/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/bundle.json","state":"https://pith.science/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6NWXL5ABXLA6J5LAQYHRF3UBME/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6NWXL5ABXLA6J5LAQYHRF3UBME","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":"a7bb066ae44b2ef78e8040c7c794df519b14fadb8199123537e67842d24f79d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-26T12:45:01Z","title_canon_sha256":"5c21439690a34fe59a8ff03441c70c950fffa2678f3dc207833331dc7a102912"},"schema_version":"1.0","source":{"id":"2505.19920","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19920","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19920v1","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19920","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_12","alias_value":"6NWXL5ABXLA6","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_16","alias_value":"6NWXL5ABXLA6J5LA","created_at":"2026-07-05T11:09:49Z"},{"alias_kind":"pith_short_8","alias_value":"6NWXL5AB","created_at":"2026-07-05T11:09:49Z"}],"graph_snapshots":[{"event_id":"sha256:06fc3d842457da76213c4767d36833740cda133414962eb7220278123d7920a9","target":"graph","created_at":"2026-07-05T11:09:49Z","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/2505.19920/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional face recognition systems rely on extracting fixed face representations, known as templates, to store and verify identities. These representations are typically generated by neural networks that often lack explainability and raise concerns regarding fairness and privacy. In this work, we propose a novel model-template (MOTE) approach that replaces vector-based face templates with small personalized neural networks. This design enables more responsible face recognition for small and medium-scale systems. During enrollment, MOTE creates a dedicated binary classifier for each identity,","authors_text":"Philipp Terh\\\"orst, Sebastian Gro{\\ss}, Stefan Heindorf","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-26T12:45:01Z","title":"A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19920","kind":"arxiv","version":1},"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:a3db0ec1456944600bba9da7f560c3d8197234b02c7ee744cc6420fb7662462c","target":"record","created_at":"2026-07-05T11:09:49Z","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":"a7bb066ae44b2ef78e8040c7c794df519b14fadb8199123537e67842d24f79d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-26T12:45:01Z","title_canon_sha256":"5c21439690a34fe59a8ff03441c70c950fffa2678f3dc207833331dc7a102912"},"schema_version":"1.0","source":{"id":"2505.19920","kind":"arxiv","version":1}},"canonical_sha256":"f36d75f401bac1e4f560860f12ee81611809472944f613655c5a131f17c2ff16","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f36d75f401bac1e4f560860f12ee81611809472944f613655c5a131f17c2ff16","first_computed_at":"2026-07-05T11:09:49.900724Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:49.900724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1287hpn2hMd0SDuW1+VFcsTO3ICFB0AdrWg9xaC3agrU+pZ+DwMkcEC/tIpGOZS8hhH/bvyvjyuO/vVsurkxBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:49.901211Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.19920","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a3db0ec1456944600bba9da7f560c3d8197234b02c7ee744cc6420fb7662462c","sha256:06fc3d842457da76213c4767d36833740cda133414962eb7220278123d7920a9"],"state_sha256":"001527dffa66dcc46ad6219ce7b4761dbea7fc749ce0342867c0342d31e4a9fe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rvERb9R/hsHuSS9Zm/XlxMiVJI/6cMPoGwl9VopJXcG3l86EpSmrJ4BKgyCuyC3N4jIH/Y9NaBcFtKB93IuQCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T06:30:42.132959Z","bundle_sha256":"ed5f8c204473b7660cffeb1fadf7caec8385beb4b76e02a8ff86d0a006292cb5"}}