{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:ZUZRM53W7QVP7JUAH767VSHYAM","short_pith_number":"pith:ZUZRM53W","schema_version":"1.0","canonical_sha256":"cd33167776fc2affa6803ffdfac8f8030a4ab9ccfdffc4a35eca18a9bfabf604","source":{"kind":"arxiv","id":"2606.23593","version":1},"attestation_state":"computed","paper":{"title":"Real-Time Multimodal Activity-Aware Error Detection in Robot-Assisted Surgery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Homa Alemzadeh, Seyed Hamid Reza Roodabeh, Zongyu Li","submitted_at":"2026-06-22T17:01:45Z","abstract_excerpt":"Robot-assisted minimally invasive surgery improves surgical precision but introduces complexity, making technical error detection essential for ensuring patient safety. Current executional error detection methods using video data often overlook fine-grained contextual descriptions of activities and error types within the hierarchical structure of surgical procedures. They also under-utilize complementary multimodal information. We propose a unified framework for executional error detection that leverages multimodal input, including video, kinematics, and descriptive textual prompts. Through ac"},"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":"2606.23593","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-06-22T17:01:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"7d76050eaf7873b2062ad269c6b9b5c8cac83476f69f8bb9bc89fd92a6a0b215","abstract_canon_sha256":"8c0502c09da0c19c9b8f19c098328b26e47f673dab078debc15e9238ec0a69cd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T03:14:31.806582Z","signature_b64":"833N9M6XckNg2fg5041B+DGGn36fAXKrMpZJXEmh949bXmAXf9bKHk/Kzs0ZNZEhptd8psezNP1jNCTrjT7OBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd33167776fc2affa6803ffdfac8f8030a4ab9ccfdffc4a35eca18a9bfabf604","last_reissued_at":"2026-06-23T03:14:31.806198Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T03:14:31.806198Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Real-Time Multimodal Activity-Aware Error Detection in Robot-Assisted Surgery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Homa Alemzadeh, Seyed Hamid Reza Roodabeh, Zongyu Li","submitted_at":"2026-06-22T17:01:45Z","abstract_excerpt":"Robot-assisted minimally invasive surgery improves surgical precision but introduces complexity, making technical error detection essential for ensuring patient safety. Current executional error detection methods using video data often overlook fine-grained contextual descriptions of activities and error types within the hierarchical structure of surgical procedures. They also under-utilize complementary multimodal information. We propose a unified framework for executional error detection that leverages multimodal input, including video, kinematics, and descriptive textual prompts. Through ac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23593","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/2606.23593/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.23593","created_at":"2026-06-23T03:14:31.806254+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.23593v1","created_at":"2026-06-23T03:14:31.806254+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23593","created_at":"2026-06-23T03:14:31.806254+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZUZRM53W7QVP","created_at":"2026-06-23T03:14:31.806254+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZUZRM53W7QVP7JUA","created_at":"2026-06-23T03:14:31.806254+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZUZRM53W","created_at":"2026-06-23T03:14:31.806254+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/ZUZRM53W7QVP7JUAH767VSHYAM","json":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM.json","graph_json":"https://pith.science/api/pith-number/ZUZRM53W7QVP7JUAH767VSHYAM/graph.json","events_json":"https://pith.science/api/pith-number/ZUZRM53W7QVP7JUAH767VSHYAM/events.json","paper":"https://pith.science/paper/ZUZRM53W"},"agent_actions":{"view_html":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM","download_json":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM.json","view_paper":"https://pith.science/paper/ZUZRM53W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.23593&json=true","fetch_graph":"https://pith.science/api/pith-number/ZUZRM53W7QVP7JUAH767VSHYAM/graph.json","fetch_events":"https://pith.science/api/pith-number/ZUZRM53W7QVP7JUAH767VSHYAM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM/action/storage_attestation","attest_author":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM/action/author_attestation","sign_citation":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM/action/citation_signature","submit_replication":"https://pith.science/pith/ZUZRM53W7QVP7JUAH767VSHYAM/action/replication_record"}},"created_at":"2026-06-23T03:14:31.806254+00:00","updated_at":"2026-06-23T03:14:31.806254+00:00"}