{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:W5C2PYY43CX7Y6DA7KAYQ7KRWN","short_pith_number":"pith:W5C2PYY4","schema_version":"1.0","canonical_sha256":"b745a7e31cd8affc7860fa81887d51b361bb3de0e1723fd2918edc8aab542195","source":{"kind":"arxiv","id":"2605.14845","version":1},"attestation_state":"computed","paper":{"title":"Exploring Vision-Language Models for Online Signature Verification: A Zero-Shot Capability Study","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Javier Ortega-Garcia, Marta Robledo-Moreno, Ruben Tolosana, Ruben Vera-Rodriguez","submitted_at":"2026-05-14T13:53:28Z","abstract_excerpt":"Recent advancements in Vision-Language Models (VLMs) have demonstrated strong capabilities in general visual reasoning, yet their applicability to rigorous biometric tasks remains unexplored. This work presents an exploratory study evaluating the zero-shot performance of state-of-the-art VLMs (GPT-5.2 and Gemini 2.5 Pro) on the Signature Verification Challenge (SVC) benchmark. To enable visual processing, raw kinematic time-series are converted into static images, encoding pressure information into stroke opacity whenever available in the source data. Furthermore, we introduce a scoring protoc"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.14845","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T13:53:28Z","cross_cats_sorted":[],"title_canon_sha256":"b19fbf0ed340e852ec93a527100705dc57ce85b920b872a86175fc409e7e0ce8","abstract_canon_sha256":"31459c9f2a92ba1674e774cbe019b3f327b0f0240b2113f0d8e1122f19764b0b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:38:56.378073Z","signature_b64":"YWubAH8x/UZLcka8WzdbLzG8nC8htXdV9U6o3PTT6/0z7x2jVcUCiMIwFW6uyRzGZsELAJtD+gwByhENNCDuAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b745a7e31cd8affc7860fa81887d51b361bb3de0e1723fd2918edc8aab542195","last_reissued_at":"2026-05-17T23:38:56.377383Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:38:56.377383Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exploring Vision-Language Models for Online Signature Verification: A Zero-Shot Capability Study","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Javier Ortega-Garcia, Marta Robledo-Moreno, Ruben Tolosana, Ruben Vera-Rodriguez","submitted_at":"2026-05-14T13:53:28Z","abstract_excerpt":"Recent advancements in Vision-Language Models (VLMs) have demonstrated strong capabilities in general visual reasoning, yet their applicability to rigorous biometric tasks remains unexplored. This work presents an exploratory study evaluating the zero-shot performance of state-of-the-art VLMs (GPT-5.2 and Gemini 2.5 Pro) on the Signature Verification Challenge (SVC) benchmark. To enable visual processing, raw kinematic time-series are converted into static images, encoding pressure information into stroke opacity whenever available in the source data. Furthermore, we introduce a scoring protoc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14845","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.14845","created_at":"2026-05-17T23:38:56.377493+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.14845v1","created_at":"2026-05-17T23:38:56.377493+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14845","created_at":"2026-05-17T23:38:56.377493+00:00"},{"alias_kind":"pith_short_12","alias_value":"W5C2PYY43CX7","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_16","alias_value":"W5C2PYY43CX7Y6DA","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_8","alias_value":"W5C2PYY4","created_at":"2026-05-18T12:33:37.589309+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN","json":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN.json","graph_json":"https://pith.science/api/pith-number/W5C2PYY43CX7Y6DA7KAYQ7KRWN/graph.json","events_json":"https://pith.science/api/pith-number/W5C2PYY43CX7Y6DA7KAYQ7KRWN/events.json","paper":"https://pith.science/paper/W5C2PYY4"},"agent_actions":{"view_html":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN","download_json":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN.json","view_paper":"https://pith.science/paper/W5C2PYY4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.14845&json=true","fetch_graph":"https://pith.science/api/pith-number/W5C2PYY43CX7Y6DA7KAYQ7KRWN/graph.json","fetch_events":"https://pith.science/api/pith-number/W5C2PYY43CX7Y6DA7KAYQ7KRWN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN/action/storage_attestation","attest_author":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN/action/author_attestation","sign_citation":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN/action/citation_signature","submit_replication":"https://pith.science/pith/W5C2PYY43CX7Y6DA7KAYQ7KRWN/action/replication_record"}},"created_at":"2026-05-17T23:38:56.377493+00:00","updated_at":"2026-05-17T23:38:56.377493+00:00"}