{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:G24CRQ4AE2IBR43TBJHBEF3HWO","short_pith_number":"pith:G24CRQ4A","canonical_record":{"source":{"id":"2405.18291","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T15:43:29Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"7083a57cd894d8cde89678937358869960f923fe3cb52a6e3370798c08edaa80","abstract_canon_sha256":"a68423ec50a750256c4c6ea24e306e7d532124dc9146ab4ccc38958c4a9b3931"},"schema_version":"1.0"},"canonical_sha256":"36b828c380269018f3730a4e121767b3af50b496520730b22b0461026a65563b","source":{"kind":"arxiv","id":"2405.18291","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18291","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18291v1","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18291","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_12","alias_value":"G24CRQ4AE2IB","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_16","alias_value":"G24CRQ4AE2IBR43T","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_8","alias_value":"G24CRQ4A","created_at":"2026-07-05T08:24:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:G24CRQ4AE2IBR43TBJHBEF3HWO","target":"record","payload":{"canonical_record":{"source":{"id":"2405.18291","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T15:43:29Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"7083a57cd894d8cde89678937358869960f923fe3cb52a6e3370798c08edaa80","abstract_canon_sha256":"a68423ec50a750256c4c6ea24e306e7d532124dc9146ab4ccc38958c4a9b3931"},"schema_version":"1.0"},"canonical_sha256":"36b828c380269018f3730a4e121767b3af50b496520730b22b0461026a65563b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:18.071727Z","signature_b64":"SQTfO01sXxHK1fJrKGh2Uru9t2V+sEIZlmaN4ymP1TUxzJzag1wwrdy+XZz0zu1bpcMrv4nJd85YTRBipWvuAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36b828c380269018f3730a4e121767b3af50b496520730b22b0461026a65563b","last_reissued_at":"2026-07-05T08:24:18.071219Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:18.071219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.18291","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":"2026-07-05T08:24:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s88+hVqDt2WJAisLipwGk1xscyLo9glyeGx6VrOT6h2D6Q4/qxVRmDkEngfZhHtWEG0NK1ThF9TCZnp6VO3vAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T04:19:01.439496Z"},"content_sha256":"9a15617ba50b9075c7e7140afea0099571781e6e5a51cff3f073e74edd19fb60","schema_version":"1.0","event_id":"sha256:9a15617ba50b9075c7e7140afea0099571781e6e5a51cff3f073e74edd19fb60"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:G24CRQ4AE2IBR43TBJHBEF3HWO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Chenglu Wen, Cheng Wang, Lingjuan Lyu, Rongshan Yu, Xiaoliang Fan, Zhaopeng Peng, Zheng Wang, Zhicheng Yang, Zihui Wang","submitted_at":"2024-05-28T15:43:29Z","abstract_excerpt":"Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. Existing methods primarily focus on adjusting gradient allocations among clients to achieve collaborative fairness. However, they frequently overlook crucial factors such as maintaining consistency across local models and catering to the diverse requirements of high-contributing clients. This oversight inevitably decreases both fairness and model accuracy in practice. To address these issues, we propose FedSAC, a nove"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18291","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/2405.18291/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":"2026-07-05T08:24:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AGCUw5o5XbYKtar8WJn1cUP7d4J0uI3UiXsxKFPd4lMIO2moMx34+PXOsvuKMbfRvv3lLly6o2ctqUFiOGHtBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T04:19:01.440156Z"},"content_sha256":"4260cc6e8f39d14f0ac1437600ff92851a8992542ba4223b938446efc329e5f0","schema_version":"1.0","event_id":"sha256:4260cc6e8f39d14f0ac1437600ff92851a8992542ba4223b938446efc329e5f0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/bundle.json","state_url":"https://pith.science/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/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":"2026-08-18T04:19:01Z","links":{"resolver":"https://pith.science/pith/G24CRQ4AE2IBR43TBJHBEF3HWO","bundle":"https://pith.science/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/bundle.json","state":"https://pith.science/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G24CRQ4AE2IBR43TBJHBEF3HWO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:G24CRQ4AE2IBR43TBJHBEF3HWO","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":"a68423ec50a750256c4c6ea24e306e7d532124dc9146ab4ccc38958c4a9b3931","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T15:43:29Z","title_canon_sha256":"7083a57cd894d8cde89678937358869960f923fe3cb52a6e3370798c08edaa80"},"schema_version":"1.0","source":{"id":"2405.18291","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18291","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18291v1","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18291","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_12","alias_value":"G24CRQ4AE2IB","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_16","alias_value":"G24CRQ4AE2IBR43T","created_at":"2026-07-05T08:24:18Z"},{"alias_kind":"pith_short_8","alias_value":"G24CRQ4A","created_at":"2026-07-05T08:24:18Z"}],"graph_snapshots":[{"event_id":"sha256:4260cc6e8f39d14f0ac1437600ff92851a8992542ba4223b938446efc329e5f0","target":"graph","created_at":"2026-07-05T08:24:18Z","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/2405.18291/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. Existing methods primarily focus on adjusting gradient allocations among clients to achieve collaborative fairness. However, they frequently overlook crucial factors such as maintaining consistency across local models and catering to the diverse requirements of high-contributing clients. This oversight inevitably decreases both fairness and model accuracy in practice. To address these issues, we propose FedSAC, a nove","authors_text":"Chenglu Wen, Cheng Wang, Lingjuan Lyu, Rongshan Yu, Xiaoliang Fan, Zhaopeng Peng, Zheng Wang, Zhicheng Yang, Zihui Wang","cross_cats":["cs.AI","cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T15:43:29Z","title":"FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18291","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":"sha256:9a15617ba50b9075c7e7140afea0099571781e6e5a51cff3f073e74edd19fb60","target":"record","created_at":"2026-07-05T08:24:18Z","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":"a68423ec50a750256c4c6ea24e306e7d532124dc9146ab4ccc38958c4a9b3931","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-28T15:43:29Z","title_canon_sha256":"7083a57cd894d8cde89678937358869960f923fe3cb52a6e3370798c08edaa80"},"schema_version":"1.0","source":{"id":"2405.18291","kind":"arxiv","version":1}},"canonical_sha256":"36b828c380269018f3730a4e121767b3af50b496520730b22b0461026a65563b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36b828c380269018f3730a4e121767b3af50b496520730b22b0461026a65563b","first_computed_at":"2026-07-05T08:24:18.071219Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:18.071219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SQTfO01sXxHK1fJrKGh2Uru9t2V+sEIZlmaN4ymP1TUxzJzag1wwrdy+XZz0zu1bpcMrv4nJd85YTRBipWvuAg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:18.071727Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.18291","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a15617ba50b9075c7e7140afea0099571781e6e5a51cff3f073e74edd19fb60","sha256:4260cc6e8f39d14f0ac1437600ff92851a8992542ba4223b938446efc329e5f0"],"state_sha256":"baf793f167c125cba7e3da81e4efcbaef31f5d3b2ac0200472b45acc91d95dde"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CFOhbeEleE+uDz5kAgHBCO7rvBoCM+omTvvu4w9zriLgTEJDn/6ZOEztVB1IIAGt7Oaf9KoYz3GancsQmMhmBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T04:19:01.450644Z","bundle_sha256":"e2eb7c09fd7f8139968d4083b0b4b6843cc5f4c1463c2b1cbc4578c96ea09548"}}