{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:E6NHSJDLP5OONGQ36UXOZNCOO7","short_pith_number":"pith:E6NHSJDL","canonical_record":{"source":{"id":"2505.11439","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T16:58:03Z","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"title_canon_sha256":"67ab2c6686d1f0ea6a018d6f019f66033b79de91e80b94ef33230f008e3e91b0","abstract_canon_sha256":"60e62307d1ee31f9fb35cdc23c83ad51925b7276bcb26abdf6f788d76ba19b02"},"schema_version":"1.0"},"canonical_sha256":"279a79246b7f5ce69a1bf52eecb44e77ce01255384b5e9cafcfb3c9068bf3dcd","source":{"kind":"arxiv","id":"2505.11439","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11439","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11439v1","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11439","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_12","alias_value":"E6NHSJDLP5OO","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_16","alias_value":"E6NHSJDLP5OONGQ3","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_8","alias_value":"E6NHSJDL","created_at":"2026-07-05T11:04:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:E6NHSJDLP5OONGQ36UXOZNCOO7","target":"record","payload":{"canonical_record":{"source":{"id":"2505.11439","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T16:58:03Z","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"title_canon_sha256":"67ab2c6686d1f0ea6a018d6f019f66033b79de91e80b94ef33230f008e3e91b0","abstract_canon_sha256":"60e62307d1ee31f9fb35cdc23c83ad51925b7276bcb26abdf6f788d76ba19b02"},"schema_version":"1.0"},"canonical_sha256":"279a79246b7f5ce69a1bf52eecb44e77ce01255384b5e9cafcfb3c9068bf3dcd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:04:16.312751Z","signature_b64":"xwK9g8uniYPhBAeyt/rWK/wDC5KDaDlpYglw0Y+2sMVaS+jyfw7U9C/qFghhKA6AT9vdJG+dHSwIp8oV7IZ4AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"279a79246b7f5ce69a1bf52eecb44e77ce01255384b5e9cafcfb3c9068bf3dcd","last_reissued_at":"2026-07-05T11:04:16.312174Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:04:16.312174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.11439","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":"2026-07-05T11:04:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IBnIjpJtL3YxfFG1mmmdVfDN5Kbyd24BSOf3RlxZmq8tV+wuVGsGXeg3DklrhA5BfbwgJ9xw0HZGnNcwak9iBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:10:10.724264Z"},"content_sha256":"db780d7b764391b880f4a2a803fd7b3ff282f9516485099bc4a22f1b610c86f9","schema_version":"1.0","event_id":"sha256:db780d7b764391b880f4a2a803fd7b3ff282f9516485099bc4a22f1b610c86f9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:E6NHSJDLP5OONGQ36UXOZNCOO7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"Haozheng Xu, Stamatia Giannarou, Utsav Rai","submitted_at":"2025-05-16T16:58:03Z","abstract_excerpt":"Accurate pose estimation of surgical tools in Robot-assisted Minimally Invasive Surgery (RMIS) is essential for surgical navigation and robot control. While traditional marker-based methods offer accuracy, they face challenges with occlusions, reflections, and tool-specific designs. Similarly, supervised learning methods require extensive training on annotated datasets, limiting their adaptability to new tools. Despite their success in other domains, zero-shot pose estimation models remain unexplored in RMIS for pose estimation of surgical instruments, creating a gap in generalising to unseen "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11439","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/2505.11439/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":"2026-07-05T11:04:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FOaZv1eyk5QHxVx2TyYK3GixQHkoAd+lnrtC8txfplWAk0x2NRG2XsunEX4/EXdr7c52T1uJFVKqlIw3PgNLBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:10:10.724892Z"},"content_sha256":"eaa81f5dc68df8d1840a939d30dc56391c48456b93113775c28699b0ed4a6bd8","schema_version":"1.0","event_id":"sha256:eaa81f5dc68df8d1840a939d30dc56391c48456b93113775c28699b0ed4a6bd8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/bundle.json","state_url":"https://pith.science/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/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":"2026-08-06T01:10:10Z","links":{"resolver":"https://pith.science/pith/E6NHSJDLP5OONGQ36UXOZNCOO7","bundle":"https://pith.science/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/bundle.json","state":"https://pith.science/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E6NHSJDLP5OONGQ36UXOZNCOO7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:E6NHSJDLP5OONGQ36UXOZNCOO7","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":"60e62307d1ee31f9fb35cdc23c83ad51925b7276bcb26abdf6f788d76ba19b02","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T16:58:03Z","title_canon_sha256":"67ab2c6686d1f0ea6a018d6f019f66033b79de91e80b94ef33230f008e3e91b0"},"schema_version":"1.0","source":{"id":"2505.11439","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11439","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11439v1","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11439","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_12","alias_value":"E6NHSJDLP5OO","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_16","alias_value":"E6NHSJDLP5OONGQ3","created_at":"2026-07-05T11:04:16Z"},{"alias_kind":"pith_short_8","alias_value":"E6NHSJDL","created_at":"2026-07-05T11:04:16Z"}],"graph_snapshots":[{"event_id":"sha256:eaa81f5dc68df8d1840a939d30dc56391c48456b93113775c28699b0ed4a6bd8","target":"graph","created_at":"2026-07-05T11:04:16Z","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/2505.11439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate pose estimation of surgical tools in Robot-assisted Minimally Invasive Surgery (RMIS) is essential for surgical navigation and robot control. While traditional marker-based methods offer accuracy, they face challenges with occlusions, reflections, and tool-specific designs. Similarly, supervised learning methods require extensive training on annotated datasets, limiting their adaptability to new tools. Despite their success in other domains, zero-shot pose estimation models remain unexplored in RMIS for pose estimation of surgical instruments, creating a gap in generalising to unseen ","authors_text":"Haozheng Xu, Stamatia Giannarou, Utsav Rai","cross_cats":["cs.AI","cs.LG","cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T16:58:03Z","title":"SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11439","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:db780d7b764391b880f4a2a803fd7b3ff282f9516485099bc4a22f1b610c86f9","target":"record","created_at":"2026-07-05T11:04:16Z","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":"60e62307d1ee31f9fb35cdc23c83ad51925b7276bcb26abdf6f788d76ba19b02","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-16T16:58:03Z","title_canon_sha256":"67ab2c6686d1f0ea6a018d6f019f66033b79de91e80b94ef33230f008e3e91b0"},"schema_version":"1.0","source":{"id":"2505.11439","kind":"arxiv","version":1}},"canonical_sha256":"279a79246b7f5ce69a1bf52eecb44e77ce01255384b5e9cafcfb3c9068bf3dcd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"279a79246b7f5ce69a1bf52eecb44e77ce01255384b5e9cafcfb3c9068bf3dcd","first_computed_at":"2026-07-05T11:04:16.312174Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:16.312174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xwK9g8uniYPhBAeyt/rWK/wDC5KDaDlpYglw0Y+2sMVaS+jyfw7U9C/qFghhKA6AT9vdJG+dHSwIp8oV7IZ4AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:16.312751Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11439","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:db780d7b764391b880f4a2a803fd7b3ff282f9516485099bc4a22f1b610c86f9","sha256:eaa81f5dc68df8d1840a939d30dc56391c48456b93113775c28699b0ed4a6bd8"],"state_sha256":"7feca7cf96cbe28464e558b6b53d5c71c183ab5ca5a19748b13a994d415debab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OOjLqz+qOBJ8hqFsKNRbUdddCklct/n8NHlCK+LwgudC/3xxkMhkuXvRTHHvUuZH3HGsgsmX8uFF/spSF9gRBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T01:10:10.730568Z","bundle_sha256":"c1ff4bdc04d4fa6c6a36048299eab403bf9b567bd442333a28228e7d9433b024"}}