{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5NZ3CNRTJZECOJJMN5LL67KWKT","short_pith_number":"pith:5NZ3CNRT","schema_version":"1.0","canonical_sha256":"eb73b136334e4827252c6f56bf7d5654c47c6e433ca744c41409a9456db933ce","source":{"kind":"arxiv","id":"2412.16597","version":2},"attestation_state":"computed","paper":{"title":"LLMs Enable Context-Aware Augmented Reality in Surgical Navigation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Gregor Alexander Stavrou, Hamraz Javaheri, Jakob Karolus, Omid Ghamarnejad, Paul Lukowicz","submitted_at":"2024-12-21T12:03:31Z","abstract_excerpt":"Wearable Augmented Reality (AR) technologies are gaining recognition for their potential to transform surgical navigation systems. As these technologies evolve, selecting the right interaction method to control the system becomes crucial. Our work introduces a voice-controlled user interface (VCUI) for surgical AR assistance systems (ARAS), designed for pancreatic surgery, that integrates Large Language Models (LLMs). Employing a mixed-method research approach, we assessed the usability of our LLM-based design in both simulated surgical tasks and during pancreatic surgeries, comparing its perf"},"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":"2412.16597","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.HC","submitted_at":"2024-12-21T12:03:31Z","cross_cats_sorted":[],"title_canon_sha256":"28d7bccb8ec54c1db33021b50973fc35822133c55808eef7b631d849aa387ca1","abstract_canon_sha256":"e83c5fdc121a332d4ea49bccc4591dd097b52ab5630c32f87da026c4e90133b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:47.553610Z","signature_b64":"KMoQKYcisgzm+Vf7phXgEQajh24GmkrDgyhc1Eeg8juFwqwDI1EUgqhrIqBIthe54yEPO1sxQ/RG/AQmfFv+AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb73b136334e4827252c6f56bf7d5654c47c6e433ca744c41409a9456db933ce","last_reissued_at":"2026-07-05T09:53:47.553152Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:47.553152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLMs Enable Context-Aware Augmented Reality in Surgical Navigation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Gregor Alexander Stavrou, Hamraz Javaheri, Jakob Karolus, Omid Ghamarnejad, Paul Lukowicz","submitted_at":"2024-12-21T12:03:31Z","abstract_excerpt":"Wearable Augmented Reality (AR) technologies are gaining recognition for their potential to transform surgical navigation systems. As these technologies evolve, selecting the right interaction method to control the system becomes crucial. Our work introduces a voice-controlled user interface (VCUI) for surgical AR assistance systems (ARAS), designed for pancreatic surgery, that integrates Large Language Models (LLMs). Employing a mixed-method research approach, we assessed the usability of our LLM-based design in both simulated surgical tasks and during pancreatic surgeries, comparing its perf"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16597","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.16597/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":"2412.16597","created_at":"2026-07-05T09:53:47.553210+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.16597v2","created_at":"2026-07-05T09:53:47.553210+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16597","created_at":"2026-07-05T09:53:47.553210+00:00"},{"alias_kind":"pith_short_12","alias_value":"5NZ3CNRTJZEC","created_at":"2026-07-05T09:53:47.553210+00:00"},{"alias_kind":"pith_short_16","alias_value":"5NZ3CNRTJZECOJJM","created_at":"2026-07-05T09:53:47.553210+00:00"},{"alias_kind":"pith_short_8","alias_value":"5NZ3CNRT","created_at":"2026-07-05T09:53:47.553210+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2608.07861","citing_title":"How Much Does It Cost to Answer My Question? Benchmarking Cloud VLM-based VQA Systems","ref_index":11,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT","json":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT.json","graph_json":"https://pith.science/api/pith-number/5NZ3CNRTJZECOJJMN5LL67KWKT/graph.json","events_json":"https://pith.science/api/pith-number/5NZ3CNRTJZECOJJMN5LL67KWKT/events.json","paper":"https://pith.science/paper/5NZ3CNRT"},"agent_actions":{"view_html":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT","download_json":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT.json","view_paper":"https://pith.science/paper/5NZ3CNRT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.16597&json=true","fetch_graph":"https://pith.science/api/pith-number/5NZ3CNRTJZECOJJMN5LL67KWKT/graph.json","fetch_events":"https://pith.science/api/pith-number/5NZ3CNRTJZECOJJMN5LL67KWKT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT/action/storage_attestation","attest_author":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT/action/author_attestation","sign_citation":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT/action/citation_signature","submit_replication":"https://pith.science/pith/5NZ3CNRTJZECOJJMN5LL67KWKT/action/replication_record"}},"created_at":"2026-07-05T09:53:47.553210+00:00","updated_at":"2026-07-05T09:53:47.553210+00:00"}