{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:QXCYHKPC5LTPSBRE5T7ZMLFFFG","short_pith_number":"pith:QXCYHKPC","canonical_record":{"source":{"id":"2301.05392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-13T05:20:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1e135e5cd63382ca65ea7482df90fb362e36699eabed21a0f359adcf6082cf54","abstract_canon_sha256":"c14652ecfc1e4c66a36ae2a645560624a8dedba2d6d527fff31851f96205f280"},"schema_version":"1.0"},"canonical_sha256":"85c583a9e2eae6f90624ecff962ca529ace2e660821472a1c0d71b4e1a4312b2","source":{"kind":"arxiv","id":"2301.05392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.05392","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"arxiv_version","alias_value":"2301.05392v1","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.05392","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_12","alias_value":"QXCYHKPC5LTP","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_16","alias_value":"QXCYHKPC5LTPSBRE","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_8","alias_value":"QXCYHKPC","created_at":"2026-07-05T05:32:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:QXCYHKPC5LTPSBRE5T7ZMLFFFG","target":"record","payload":{"canonical_record":{"source":{"id":"2301.05392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-13T05:20:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1e135e5cd63382ca65ea7482df90fb362e36699eabed21a0f359adcf6082cf54","abstract_canon_sha256":"c14652ecfc1e4c66a36ae2a645560624a8dedba2d6d527fff31851f96205f280"},"schema_version":"1.0"},"canonical_sha256":"85c583a9e2eae6f90624ecff962ca529ace2e660821472a1c0d71b4e1a4312b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:32:52.458238Z","signature_b64":"9Aiwvh8gYdH0i1ieiCHhu9u9hmB5wNY9SywCif4q1owP6JfOBZNEMPYyyraQxG/PosANpDw2vNIudj/bnTgrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"85c583a9e2eae6f90624ecff962ca529ace2e660821472a1c0d71b4e1a4312b2","last_reissued_at":"2026-07-05T05:32:52.457763Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:32:52.457763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.05392","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":"2026-07-05T05:32:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x5hWX7d95cS3aTNUkYczonQVejsdFThDB1IPDpkmwmdYblp+xJDp55SQDIDrC2mmM0rMa/57kvcviHYXwIsEBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:16:08.430116Z"},"content_sha256":"58604b03f5f0b34a65ff26a0de38fcd1945c4a749d436596c331166e55306b00","schema_version":"1.0","event_id":"sha256:58604b03f5f0b34a65ff26a0de38fcd1945c4a749d436596c331166e55306b00"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:QXCYHKPC5LTPSBRE5T7ZMLFFFG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Dengqiang Jia, Fuping Wu, Huandong Lin, Kaiwen Wan, Lei Li, Shangqi Gao, Sijia Wang, Wei Qian, Xiahai Zhuang, Xin Gao, Xiongzheng Mu, Yingzhi Wu","submitted_at":"2023-01-13T05:20:07Z","abstract_excerpt":"Medical images are generally acquired with limited field-of-view (FOV), which could lead to incomplete regions of interest (ROI), and thus impose a great challenge on medical image analysis. This is particularly evident for the learning-based multi-target landmark detection, where algorithms could be misleading to learn primarily the variation of background due to the varying FOV, failing the detection of targets. Based on learning a navigation policy, instead of predicting targets directly, reinforcement learning (RL)-based methods have the potential totackle this challenge in an efficient ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.05392","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/2301.05392/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":"2026-07-05T05:32:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LJ16V8e4vme39+jFmkpziqVA6wMW1GqKV+2TdnjwceNSchSUb/gAIt64wVrlOyZZ9ggHXQj1PGaauEJdGildCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:16:08.430612Z"},"content_sha256":"915a642712816524bb0ef1d9d57e4752d50364eb2581d11bbebd28f39abf2536","schema_version":"1.0","event_id":"sha256:915a642712816524bb0ef1d9d57e4752d50364eb2581d11bbebd28f39abf2536"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/bundle.json","state_url":"https://pith.science/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/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":"2026-08-06T18:16:08Z","links":{"resolver":"https://pith.science/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG","bundle":"https://pith.science/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/bundle.json","state":"https://pith.science/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QXCYHKPC5LTPSBRE5T7ZMLFFFG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:QXCYHKPC5LTPSBRE5T7ZMLFFFG","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":"c14652ecfc1e4c66a36ae2a645560624a8dedba2d6d527fff31851f96205f280","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-13T05:20:07Z","title_canon_sha256":"1e135e5cd63382ca65ea7482df90fb362e36699eabed21a0f359adcf6082cf54"},"schema_version":"1.0","source":{"id":"2301.05392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.05392","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"arxiv_version","alias_value":"2301.05392v1","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.05392","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_12","alias_value":"QXCYHKPC5LTP","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_16","alias_value":"QXCYHKPC5LTPSBRE","created_at":"2026-07-05T05:32:52Z"},{"alias_kind":"pith_short_8","alias_value":"QXCYHKPC","created_at":"2026-07-05T05:32:52Z"}],"graph_snapshots":[{"event_id":"sha256:915a642712816524bb0ef1d9d57e4752d50364eb2581d11bbebd28f39abf2536","target":"graph","created_at":"2026-07-05T05:32:52Z","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/2301.05392/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical images are generally acquired with limited field-of-view (FOV), which could lead to incomplete regions of interest (ROI), and thus impose a great challenge on medical image analysis. This is particularly evident for the learning-based multi-target landmark detection, where algorithms could be misleading to learn primarily the variation of background due to the varying FOV, failing the detection of targets. Based on learning a navigation policy, instead of predicting targets directly, reinforcement learning (RL)-based methods have the potential totackle this challenge in an efficient ma","authors_text":"Dengqiang Jia, Fuping Wu, Huandong Lin, Kaiwen Wan, Lei Li, Shangqi Gao, Sijia Wang, Wei Qian, Xiahai Zhuang, Xin Gao, Xiongzheng Mu, Yingzhi Wu","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-13T05:20:07Z","title":"Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.05392","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":"sha256:58604b03f5f0b34a65ff26a0de38fcd1945c4a749d436596c331166e55306b00","target":"record","created_at":"2026-07-05T05:32:52Z","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":"c14652ecfc1e4c66a36ae2a645560624a8dedba2d6d527fff31851f96205f280","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-13T05:20:07Z","title_canon_sha256":"1e135e5cd63382ca65ea7482df90fb362e36699eabed21a0f359adcf6082cf54"},"schema_version":"1.0","source":{"id":"2301.05392","kind":"arxiv","version":1}},"canonical_sha256":"85c583a9e2eae6f90624ecff962ca529ace2e660821472a1c0d71b4e1a4312b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85c583a9e2eae6f90624ecff962ca529ace2e660821472a1c0d71b4e1a4312b2","first_computed_at":"2026-07-05T05:32:52.457763Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:32:52.457763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9Aiwvh8gYdH0i1ieiCHhu9u9hmB5wNY9SywCif4q1owP6JfOBZNEMPYyyraQxG/PosANpDw2vNIudj/bnTgrDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:32:52.458238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.05392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:58604b03f5f0b34a65ff26a0de38fcd1945c4a749d436596c331166e55306b00","sha256:915a642712816524bb0ef1d9d57e4752d50364eb2581d11bbebd28f39abf2536"],"state_sha256":"09f54f58bb0fedafe2f6515532255d6e2d26e5f3d77ad9f5ed0510f682604f22"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vN/7p+OH0bPVln8BI06XAeDYLfG4h1iF4TVlCDp+4cf9PYjIAnZQ2eBjlfnNZe3AzDowxoObCKzfkIupQzllBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T18:16:08.435790Z","bundle_sha256":"931d11aef4771962c107d7f3659d3a28639b50156892b86a5c5a90300b482dec"}}