{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:K6TCCTELKFZD6XRVU5PVTJT3IU","short_pith_number":"pith:K6TCCTEL","canonical_record":{"source":{"id":"2506.12447","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-14T10:59:00Z","cross_cats_sorted":[],"title_canon_sha256":"5943571554878beaeb1a877529bcb51d30f6f457f92a97a924069fad7c6c872c","abstract_canon_sha256":"abf6b1d324830a726a7a58e4ab30b86bacae17769ab38b67feb83ce438072540"},"schema_version":"1.0"},"canonical_sha256":"57a6214c8b51723f5e35a75f59a67b4505079398e233164ba9c90e76ebddaf45","source":{"kind":"arxiv","id":"2506.12447","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.12447","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"arxiv_version","alias_value":"2506.12447v3","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.12447","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_12","alias_value":"K6TCCTELKFZD","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_16","alias_value":"K6TCCTELKFZD6XRV","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_8","alias_value":"K6TCCTEL","created_at":"2026-07-05T11:45:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:K6TCCTELKFZD6XRVU5PVTJT3IU","target":"record","payload":{"canonical_record":{"source":{"id":"2506.12447","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-14T10:59:00Z","cross_cats_sorted":[],"title_canon_sha256":"5943571554878beaeb1a877529bcb51d30f6f457f92a97a924069fad7c6c872c","abstract_canon_sha256":"abf6b1d324830a726a7a58e4ab30b86bacae17769ab38b67feb83ce438072540"},"schema_version":"1.0"},"canonical_sha256":"57a6214c8b51723f5e35a75f59a67b4505079398e233164ba9c90e76ebddaf45","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:36.384225Z","signature_b64":"LJ+wOYvg6ebZvA93BXSEKpUwY+nfdcPZAYd1gP6kzUhiz1P/yMDCWhP8QJRy2BbZMX8bPcqkEG3LJ1Zz/fKRDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57a6214c8b51723f5e35a75f59a67b4505079398e233164ba9c90e76ebddaf45","last_reissued_at":"2026-07-05T11:45:36.383575Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:36.383575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.12447","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":"2026-07-05T11:45:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mFTerdBzxb+D68oR6iToYY2gASEv3dTtFmiUhvFQric98U8k/C1rqX5TvLl+/TUIexkh2pXGZ0rW/N9PGyjHBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:51:39.701788Z"},"content_sha256":"a677090e7183b61429aef0bc30c9934a3069b2e19138d062e08903f25a913264","schema_version":"1.0","event_id":"sha256:a677090e7183b61429aef0bc30c9934a3069b2e19138d062e08903f25a913264"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:K6TCCTELKFZD6XRVU5PVTJT3IU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CLIP-HandID: Vision-Language Model for Hand-Based Person Identification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amudhavel Jayavel, Babu Pallam, Nathanael L. Baisa","submitted_at":"2025-06-14T10:59:00Z","abstract_excerpt":"This paper introduces a novel approach to person identification using hand images, designed specifically for criminal investigations. The method is particularly valuable in serious crimes such as sexual abuse, where hand images are often the only identifiable evidence available. Our proposed method, CLIP-HandID, leverages a pre-trained foundational vision-language model - CLIP - to efficiently learn discriminative deep feature representations from hand images (input to CLIP's image encoder) using textual prompts as semantic guidance. Since hand images are labeled with indexes rather than text "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.12447","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/2506.12447/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":"2026-07-05T11:45:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xank5drNdKQ0HNdX6uYpyVmODZ46T3BVv/PSQvPcL7AVef0v9/1ZS6B/2JWtkWnuRxNdf4/upB+uNGFVCwwNCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:51:39.702336Z"},"content_sha256":"5f033bbb94e7abf3970805e3ebd29c8ef23ddfaf2a1d6059fc089d0d44bac424","schema_version":"1.0","event_id":"sha256:5f033bbb94e7abf3970805e3ebd29c8ef23ddfaf2a1d6059fc089d0d44bac424"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/bundle.json","state_url":"https://pith.science/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/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":"2026-08-08T22:51:39Z","links":{"resolver":"https://pith.science/pith/K6TCCTELKFZD6XRVU5PVTJT3IU","bundle":"https://pith.science/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/bundle.json","state":"https://pith.science/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K6TCCTELKFZD6XRVU5PVTJT3IU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:K6TCCTELKFZD6XRVU5PVTJT3IU","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":"abf6b1d324830a726a7a58e4ab30b86bacae17769ab38b67feb83ce438072540","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-14T10:59:00Z","title_canon_sha256":"5943571554878beaeb1a877529bcb51d30f6f457f92a97a924069fad7c6c872c"},"schema_version":"1.0","source":{"id":"2506.12447","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.12447","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"arxiv_version","alias_value":"2506.12447v3","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.12447","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_12","alias_value":"K6TCCTELKFZD","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_16","alias_value":"K6TCCTELKFZD6XRV","created_at":"2026-07-05T11:45:36Z"},{"alias_kind":"pith_short_8","alias_value":"K6TCCTEL","created_at":"2026-07-05T11:45:36Z"}],"graph_snapshots":[{"event_id":"sha256:5f033bbb94e7abf3970805e3ebd29c8ef23ddfaf2a1d6059fc089d0d44bac424","target":"graph","created_at":"2026-07-05T11:45:36Z","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/2506.12447/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces a novel approach to person identification using hand images, designed specifically for criminal investigations. The method is particularly valuable in serious crimes such as sexual abuse, where hand images are often the only identifiable evidence available. Our proposed method, CLIP-HandID, leverages a pre-trained foundational vision-language model - CLIP - to efficiently learn discriminative deep feature representations from hand images (input to CLIP's image encoder) using textual prompts as semantic guidance. Since hand images are labeled with indexes rather than text ","authors_text":"Amudhavel Jayavel, Babu Pallam, Nathanael L. Baisa","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-14T10:59:00Z","title":"CLIP-HandID: Vision-Language Model for Hand-Based Person Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.12447","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:a677090e7183b61429aef0bc30c9934a3069b2e19138d062e08903f25a913264","target":"record","created_at":"2026-07-05T11:45:36Z","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":"abf6b1d324830a726a7a58e4ab30b86bacae17769ab38b67feb83ce438072540","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-14T10:59:00Z","title_canon_sha256":"5943571554878beaeb1a877529bcb51d30f6f457f92a97a924069fad7c6c872c"},"schema_version":"1.0","source":{"id":"2506.12447","kind":"arxiv","version":3}},"canonical_sha256":"57a6214c8b51723f5e35a75f59a67b4505079398e233164ba9c90e76ebddaf45","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57a6214c8b51723f5e35a75f59a67b4505079398e233164ba9c90e76ebddaf45","first_computed_at":"2026-07-05T11:45:36.383575Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:36.383575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LJ+wOYvg6ebZvA93BXSEKpUwY+nfdcPZAYd1gP6kzUhiz1P/yMDCWhP8QJRy2BbZMX8bPcqkEG3LJ1Zz/fKRDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:36.384225Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.12447","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a677090e7183b61429aef0bc30c9934a3069b2e19138d062e08903f25a913264","sha256:5f033bbb94e7abf3970805e3ebd29c8ef23ddfaf2a1d6059fc089d0d44bac424"],"state_sha256":"e8e21932235d69f35993254f7f0cd81aa0cbe11437eb5a4f4aa3b0e3243160ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8vH+Nz6l97UETCKVKMIqQJ2HxyS7Wke+ruG3ZYhZQFUMdWXvpH3ISuIrDXVluVQ4R94ye3TIz61mUonDAUuHDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T22:51:39.706290Z","bundle_sha256":"547f10df321b3d526aa53e507cf68381dacc6838460b4b9bf472bcc7eb6ffb6d"}}