{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ZVGFSBU77SXXBURDBGRL4EFYXW","short_pith_number":"pith:ZVGFSBU7","canonical_record":{"source":{"id":"2304.00212","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-01T03:24:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b378e73a0754a964e40e77d4658c6c6d53a912fba19a86a5166f40e8b824d063","abstract_canon_sha256":"8a09fa9df70f26d4126f1f755a5b7d241cb4b1c1e286c41a1822b61aa0468e8c"},"schema_version":"1.0"},"canonical_sha256":"cd4c59069ffcaf70d22309a2be10b8bd8cfa8b32c511abeed95a36b8c6d07855","source":{"kind":"arxiv","id":"2304.00212","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.00212","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"arxiv_version","alias_value":"2304.00212v1","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.00212","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_12","alias_value":"ZVGFSBU77SXX","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_16","alias_value":"ZVGFSBU77SXXBURD","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_8","alias_value":"ZVGFSBU7","created_at":"2026-07-05T05:57:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ZVGFSBU77SXXBURDBGRL4EFYXW","target":"record","payload":{"canonical_record":{"source":{"id":"2304.00212","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-01T03:24:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b378e73a0754a964e40e77d4658c6c6d53a912fba19a86a5166f40e8b824d063","abstract_canon_sha256":"8a09fa9df70f26d4126f1f755a5b7d241cb4b1c1e286c41a1822b61aa0468e8c"},"schema_version":"1.0"},"canonical_sha256":"cd4c59069ffcaf70d22309a2be10b8bd8cfa8b32c511abeed95a36b8c6d07855","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:00.016155Z","signature_b64":"q8CjKiwliSsBO8m//jPZjZkPRgW77EsIYAMHbB5NqNwyJXfHXWUwgQQi0ABkumIdlY73H2H1TuyjI4j04HUNAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd4c59069ffcaf70d22309a2be10b8bd8cfa8b32c511abeed95a36b8c6d07855","last_reissued_at":"2026-07-05T05:57:00.015742Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:00.015742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.00212","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":"2026-07-05T05:57:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bOIdQ/Gd36tppUgqHhZXDJmzIyQo55d/R6/dbw0P/E2Xf+GPYVUeuGYLgdhn6QFQ1LwJoFxKNq686wnBG6OwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:28:14.594145Z"},"content_sha256":"8efba08603973033f45df5130683d5f0f46870a4d030d7555a9b2262c5e65ba4","schema_version":"1.0","event_id":"sha256:8efba08603973033f45df5130683d5f0f46870a4d030d7555a9b2262c5e65ba4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ZVGFSBU77SXXBURDBGRL4EFYXW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Bin Dong, Hexin Dong, Jiawen Yao, Jingren Zhou, Ke Yan, Le Lu, Ling Zhang, Li Zhang, Mingyan Qiu, Mingze Yuan, Xiaoli Yin, Xin Chen, Yingda Xia, Yu Shi, Zaiyi Liu, ZiFan Chen","submitted_at":"2023-04-01T03:24:03Z","abstract_excerpt":"Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically significant. A trustworthy medical AI algorithm should demonstrate its effectiveness on tail conditions to avoid clinically dangerous damage in these out-of-distribution (OOD) cases. In this paper, we adopt the concept of object queries in Mask Transformers to formulate semantic segmentation as a soft cluster assignment. The queries fit the feature-level cluster centers of inliers during training. Therefore, when performi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.00212","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/2304.00212/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":"2026-07-05T05:57:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RURTSvvAKsFLzZPUES9TOoKtLH2xRwdVJVtVeIlZJy7S/ThDm3WzUzDTCVwVCpmcPg1NrLc2QedgwmwKiQ9JCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:28:14.594689Z"},"content_sha256":"4d20036b2f1457830351a09b8799be57cf384fcca9273a8c921ff5a65cf46d7d","schema_version":"1.0","event_id":"sha256:4d20036b2f1457830351a09b8799be57cf384fcca9273a8c921ff5a65cf46d7d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/bundle.json","state_url":"https://pith.science/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/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":"2026-08-04T17:28:14Z","links":{"resolver":"https://pith.science/pith/ZVGFSBU77SXXBURDBGRL4EFYXW","bundle":"https://pith.science/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/bundle.json","state":"https://pith.science/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZVGFSBU77SXXBURDBGRL4EFYXW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZVGFSBU77SXXBURDBGRL4EFYXW","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":"8a09fa9df70f26d4126f1f755a5b7d241cb4b1c1e286c41a1822b61aa0468e8c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-01T03:24:03Z","title_canon_sha256":"b378e73a0754a964e40e77d4658c6c6d53a912fba19a86a5166f40e8b824d063"},"schema_version":"1.0","source":{"id":"2304.00212","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.00212","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"arxiv_version","alias_value":"2304.00212v1","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.00212","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_12","alias_value":"ZVGFSBU77SXX","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_16","alias_value":"ZVGFSBU77SXXBURD","created_at":"2026-07-05T05:57:00Z"},{"alias_kind":"pith_short_8","alias_value":"ZVGFSBU7","created_at":"2026-07-05T05:57:00Z"}],"graph_snapshots":[{"event_id":"sha256:4d20036b2f1457830351a09b8799be57cf384fcca9273a8c921ff5a65cf46d7d","target":"graph","created_at":"2026-07-05T05:57:00Z","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/2304.00212/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically significant. A trustworthy medical AI algorithm should demonstrate its effectiveness on tail conditions to avoid clinically dangerous damage in these out-of-distribution (OOD) cases. In this paper, we adopt the concept of object queries in Mask Transformers to formulate semantic segmentation as a soft cluster assignment. The queries fit the feature-level cluster centers of inliers during training. Therefore, when performi","authors_text":"Bin Dong, Hexin Dong, Jiawen Yao, Jingren Zhou, Ke Yan, Le Lu, Ling Zhang, Li Zhang, Mingyan Qiu, Mingze Yuan, Xiaoli Yin, Xin Chen, Yingda Xia, Yu Shi, Zaiyi Liu, ZiFan Chen","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-01T03:24:03Z","title":"Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.00212","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":"sha256:8efba08603973033f45df5130683d5f0f46870a4d030d7555a9b2262c5e65ba4","target":"record","created_at":"2026-07-05T05:57:00Z","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":"8a09fa9df70f26d4126f1f755a5b7d241cb4b1c1e286c41a1822b61aa0468e8c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-01T03:24:03Z","title_canon_sha256":"b378e73a0754a964e40e77d4658c6c6d53a912fba19a86a5166f40e8b824d063"},"schema_version":"1.0","source":{"id":"2304.00212","kind":"arxiv","version":1}},"canonical_sha256":"cd4c59069ffcaf70d22309a2be10b8bd8cfa8b32c511abeed95a36b8c6d07855","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd4c59069ffcaf70d22309a2be10b8bd8cfa8b32c511abeed95a36b8c6d07855","first_computed_at":"2026-07-05T05:57:00.015742Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:57:00.015742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q8CjKiwliSsBO8m//jPZjZkPRgW77EsIYAMHbB5NqNwyJXfHXWUwgQQi0ABkumIdlY73H2H1TuyjI4j04HUNAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:57:00.016155Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.00212","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8efba08603973033f45df5130683d5f0f46870a4d030d7555a9b2262c5e65ba4","sha256:4d20036b2f1457830351a09b8799be57cf384fcca9273a8c921ff5a65cf46d7d"],"state_sha256":"c3b672b648316b9df9d89b479c5cc9e9b7b6c10b2a36e875f35d3f8f1ef777c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XYY3gaTLQfaDSHqM1LNju5w+1ohC8Xv8P1HczcELApxHRIc9uZI9srC0sF5sAPTJ/4sK74groPAzs3Yv4fPMBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T17:28:14.599747Z","bundle_sha256":"51cb65cace8a150595d9946eba093dea3d30e6e39b05d20898dd64fa1129df34"}}