{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ZEBUNHD42QVMKZP7XVL2LT7J54","short_pith_number":"pith:ZEBUNHD4","canonical_record":{"source":{"id":"2304.06931","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-14T05:32:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"795b572147486543826d3498f9677445408aecfc95ca2cae2966e5fe9af4a7d1","abstract_canon_sha256":"640d1daffc12692030a1bb4a2f7453271cd7ecdb51cc422a1b3e0d8758be0cab"},"schema_version":"1.0"},"canonical_sha256":"c903469c7cd42ac565ffbd57a5cfe9ef271255971885316313681bdf8882fd5d","source":{"kind":"arxiv","id":"2304.06931","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06931","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06931v2","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06931","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_12","alias_value":"ZEBUNHD42QVM","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_16","alias_value":"ZEBUNHD42QVMKZP7","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_8","alias_value":"ZEBUNHD4","created_at":"2026-07-05T06:44:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ZEBUNHD42QVMKZP7XVL2LT7J54","target":"record","payload":{"canonical_record":{"source":{"id":"2304.06931","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-14T05:32:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"795b572147486543826d3498f9677445408aecfc95ca2cae2966e5fe9af4a7d1","abstract_canon_sha256":"640d1daffc12692030a1bb4a2f7453271cd7ecdb51cc422a1b3e0d8758be0cab"},"schema_version":"1.0"},"canonical_sha256":"c903469c7cd42ac565ffbd57a5cfe9ef271255971885316313681bdf8882fd5d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:44:30.714689Z","signature_b64":"S/Vso3b4EbcE372LUfX0Xom3y9egLtNtxa7yU2yTDYFDf32uy6YgxvILFQdOXUi31TUpvIVpswPbdV+gfWUgCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c903469c7cd42ac565ffbd57a5cfe9ef271255971885316313681bdf8882fd5d","last_reissued_at":"2026-07-05T06:44:30.714220Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:44:30.714220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.06931","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:44:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1GfEo77gOp+TDcb85jYyqL43/HS57FiRQ+zjXK27EhCkdNnTK7v1m3NCMEQSAZMYtzFjQLLIzLKhoVFedC1cCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T16:59:13.007190Z"},"content_sha256":"ae62caa639c225681c7ccac57750a8e1a76eb7a5516938ad900f356d9a9e6c36","schema_version":"1.0","event_id":"sha256:ae62caa639c225681c7ccac57750a8e1a76eb7a5516938ad900f356d9a9e6c36"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ZEBUNHD42QVMKZP7XVL2LT7J54","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scale Federated Learning for Label Set Mismatch in Medical Image Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Hao Chen, Luyang Luo, Zhipeng Deng","submitted_at":"2023-04-14T05:32:01Z","abstract_excerpt":"Federated learning (FL) has been introduced to the healthcare domain as a decentralized learning paradigm that allows multiple parties to train a model collaboratively without privacy leakage. However, most previous studies have assumed that every client holds an identical label set. In reality, medical specialists tend to annotate only diseases within their area of expertise or interest. This implies that label sets in each client can be different and even disjoint. In this paper, we propose the framework FedLSM to solve the problem of Label Set Mismatch. FedLSM adopts different training stra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06931","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/2304.06931/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":"2026-07-05T06:44:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tpJazl7rx3+kcTFi8q9nqxkMbAtg7DrFPK74Lr/rgotKecvMcjnDvZ5c+T2YN0/nTXxi5gN8ZZPLsmSpdWsiDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T16:59:13.007581Z"},"content_sha256":"d38a9a76bd2884783aab52dfd586689f313099e9b5c9c7bc286a2eb7886c69f2","schema_version":"1.0","event_id":"sha256:d38a9a76bd2884783aab52dfd586689f313099e9b5c9c7bc286a2eb7886c69f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/bundle.json","state_url":"https://pith.science/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/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":"2026-07-19T16:59:13Z","links":{"resolver":"https://pith.science/pith/ZEBUNHD42QVMKZP7XVL2LT7J54","bundle":"https://pith.science/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/bundle.json","state":"https://pith.science/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZEBUNHD42QVMKZP7XVL2LT7J54/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZEBUNHD42QVMKZP7XVL2LT7J54","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":"640d1daffc12692030a1bb4a2f7453271cd7ecdb51cc422a1b3e0d8758be0cab","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-14T05:32:01Z","title_canon_sha256":"795b572147486543826d3498f9677445408aecfc95ca2cae2966e5fe9af4a7d1"},"schema_version":"1.0","source":{"id":"2304.06931","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06931","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06931v2","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06931","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_12","alias_value":"ZEBUNHD42QVM","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_16","alias_value":"ZEBUNHD42QVMKZP7","created_at":"2026-07-05T06:44:30Z"},{"alias_kind":"pith_short_8","alias_value":"ZEBUNHD4","created_at":"2026-07-05T06:44:30Z"}],"graph_snapshots":[{"event_id":"sha256:d38a9a76bd2884783aab52dfd586689f313099e9b5c9c7bc286a2eb7886c69f2","target":"graph","created_at":"2026-07-05T06:44:30Z","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/2304.06931/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) has been introduced to the healthcare domain as a decentralized learning paradigm that allows multiple parties to train a model collaboratively without privacy leakage. However, most previous studies have assumed that every client holds an identical label set. In reality, medical specialists tend to annotate only diseases within their area of expertise or interest. This implies that label sets in each client can be different and even disjoint. In this paper, we propose the framework FedLSM to solve the problem of Label Set Mismatch. FedLSM adopts different training stra","authors_text":"Hao Chen, Luyang Luo, Zhipeng Deng","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-14T05:32:01Z","title":"Scale Federated Learning for Label Set Mismatch in Medical Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06931","kind":"arxiv","version":2},"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:ae62caa639c225681c7ccac57750a8e1a76eb7a5516938ad900f356d9a9e6c36","target":"record","created_at":"2026-07-05T06:44:30Z","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":"640d1daffc12692030a1bb4a2f7453271cd7ecdb51cc422a1b3e0d8758be0cab","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-14T05:32:01Z","title_canon_sha256":"795b572147486543826d3498f9677445408aecfc95ca2cae2966e5fe9af4a7d1"},"schema_version":"1.0","source":{"id":"2304.06931","kind":"arxiv","version":2}},"canonical_sha256":"c903469c7cd42ac565ffbd57a5cfe9ef271255971885316313681bdf8882fd5d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c903469c7cd42ac565ffbd57a5cfe9ef271255971885316313681bdf8882fd5d","first_computed_at":"2026-07-05T06:44:30.714220Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:44:30.714220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S/Vso3b4EbcE372LUfX0Xom3y9egLtNtxa7yU2yTDYFDf32uy6YgxvILFQdOXUi31TUpvIVpswPbdV+gfWUgCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:44:30.714689Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.06931","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae62caa639c225681c7ccac57750a8e1a76eb7a5516938ad900f356d9a9e6c36","sha256:d38a9a76bd2884783aab52dfd586689f313099e9b5c9c7bc286a2eb7886c69f2"],"state_sha256":"04695dae573a69bf71ba360229d0b4348c2b145d8a04938c06e349fb23379d77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y2NMwZBMdE2mqxGRacJDd95gn0PXtZkiXP5MegW/LXI89h4mPhiCosRWM8NUN4z+bzKiNHTUty4dlv4Ltp1MDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T16:59:13.009771Z","bundle_sha256":"cd6ea181134ab4798572e187e0fdf0116a1a4be652a72fac71106062d3c7a310"}}