{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VL3CKDRBZKXXIBC7HOI7UYCWKA","short_pith_number":"pith:VL3CKDRB","canonical_record":{"source":{"id":"2312.05807","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-10T07:38:56Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"a72ab06416cd7c75afa1ce83a1cbcb2aaa21f80e397abed8424e4a6fc60acc20","abstract_canon_sha256":"8a09f044d7eae1245b3f15d28354824bf61dcdfed83418afd69de5d3205d4063"},"schema_version":"1.0"},"canonical_sha256":"aaf6250e21caaf74045f3b91fa6056503b7a49f277e333121ba53a947f4e4567","source":{"kind":"arxiv","id":"2312.05807","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.05807","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"arxiv_version","alias_value":"2312.05807v1","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.05807","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_12","alias_value":"VL3CKDRBZKXX","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_16","alias_value":"VL3CKDRBZKXXIBC7","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_8","alias_value":"VL3CKDRB","created_at":"2026-07-05T07:22:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VL3CKDRBZKXXIBC7HOI7UYCWKA","target":"record","payload":{"canonical_record":{"source":{"id":"2312.05807","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-10T07:38:56Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"a72ab06416cd7c75afa1ce83a1cbcb2aaa21f80e397abed8424e4a6fc60acc20","abstract_canon_sha256":"8a09f044d7eae1245b3f15d28354824bf61dcdfed83418afd69de5d3205d4063"},"schema_version":"1.0"},"canonical_sha256":"aaf6250e21caaf74045f3b91fa6056503b7a49f277e333121ba53a947f4e4567","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:22:33.268934Z","signature_b64":"SWQRLmXVoLPwMkEBI+pkuXRAY9CFgc22u1oX+8F59sInwZrtOEO+xkPCsgLT6L3zATjs4k8jtzao6I0p/CgcDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aaf6250e21caaf74045f3b91fa6056503b7a49f277e333121ba53a947f4e4567","last_reissued_at":"2026-07-05T07:22:33.268542Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:22:33.268542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.05807","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":"2026-07-05T07:22:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RM+yF4ztGnnQNXzAmTzVArPdcfEvdYMsGNgjhC3AuxAN/GhkSNZtTm83tbFW0yQ0dGyBhO+3tOCQMifhHcpbBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T14:23:28.782511Z"},"content_sha256":"adba0426da812fc074f59463de0f71719387795b1c3495065262460386857350","schema_version":"1.0","event_id":"sha256:adba0426da812fc074f59463de0f71719387795b1c3495065262460386857350"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VL3CKDRBZKXXIBC7HOI7UYCWKA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Learning Empowered by Generative Content","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Jingyi Chai, Rui Ye, Siheng Chen, Xinyu Zhu, Yanfeng Wang","submitted_at":"2023-12-10T07:38:56Z","abstract_excerpt":"Federated learning (FL) enables leveraging distributed private data for model training in a privacy-preserving way. However, data heterogeneity significantly limits the performance of current FL methods. In this paper, we propose a novel FL framework termed FedGC, designed to mitigate data heterogeneity issues by diversifying private data with generative content. FedGC is a simple-to-implement framework as it only introduces a one-shot step of data generation. In data generation, we summarize three crucial and worth-exploring aspects (budget allocation, prompt design, and generation guidance) "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.05807","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/2312.05807/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":"2026-07-05T07:22:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ej6078vp7vqjgM++UIUoVTT3/kyr29aWQenF0Qoi3jEi4/6gYiIqBBKECGBVEjGgGGwGs+ovpTdT9Qa97H28CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T14:23:28.782885Z"},"content_sha256":"48034ab29a6e476b3241b7db565d997244118d2747d94ec549d354ac2d8471d7","schema_version":"1.0","event_id":"sha256:48034ab29a6e476b3241b7db565d997244118d2747d94ec549d354ac2d8471d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/bundle.json","state_url":"https://pith.science/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/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":"2026-07-28T14:23:28Z","links":{"resolver":"https://pith.science/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA","bundle":"https://pith.science/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/bundle.json","state":"https://pith.science/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VL3CKDRBZKXXIBC7HOI7UYCWKA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VL3CKDRBZKXXIBC7HOI7UYCWKA","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":"8a09f044d7eae1245b3f15d28354824bf61dcdfed83418afd69de5d3205d4063","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-10T07:38:56Z","title_canon_sha256":"a72ab06416cd7c75afa1ce83a1cbcb2aaa21f80e397abed8424e4a6fc60acc20"},"schema_version":"1.0","source":{"id":"2312.05807","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.05807","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"arxiv_version","alias_value":"2312.05807v1","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.05807","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_12","alias_value":"VL3CKDRBZKXX","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_16","alias_value":"VL3CKDRBZKXXIBC7","created_at":"2026-07-05T07:22:33Z"},{"alias_kind":"pith_short_8","alias_value":"VL3CKDRB","created_at":"2026-07-05T07:22:33Z"}],"graph_snapshots":[{"event_id":"sha256:48034ab29a6e476b3241b7db565d997244118d2747d94ec549d354ac2d8471d7","target":"graph","created_at":"2026-07-05T07:22:33Z","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/2312.05807/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) enables leveraging distributed private data for model training in a privacy-preserving way. However, data heterogeneity significantly limits the performance of current FL methods. In this paper, we propose a novel FL framework termed FedGC, designed to mitigate data heterogeneity issues by diversifying private data with generative content. FedGC is a simple-to-implement framework as it only introduces a one-shot step of data generation. In data generation, we summarize three crucial and worth-exploring aspects (budget allocation, prompt design, and generation guidance) ","authors_text":"Jingyi Chai, Rui Ye, Siheng Chen, Xinyu Zhu, Yanfeng Wang","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-10T07:38:56Z","title":"Federated Learning Empowered by Generative Content"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.05807","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:adba0426da812fc074f59463de0f71719387795b1c3495065262460386857350","target":"record","created_at":"2026-07-05T07:22:33Z","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":"8a09f044d7eae1245b3f15d28354824bf61dcdfed83418afd69de5d3205d4063","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-10T07:38:56Z","title_canon_sha256":"a72ab06416cd7c75afa1ce83a1cbcb2aaa21f80e397abed8424e4a6fc60acc20"},"schema_version":"1.0","source":{"id":"2312.05807","kind":"arxiv","version":1}},"canonical_sha256":"aaf6250e21caaf74045f3b91fa6056503b7a49f277e333121ba53a947f4e4567","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aaf6250e21caaf74045f3b91fa6056503b7a49f277e333121ba53a947f4e4567","first_computed_at":"2026-07-05T07:22:33.268542Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:22:33.268542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SWQRLmXVoLPwMkEBI+pkuXRAY9CFgc22u1oX+8F59sInwZrtOEO+xkPCsgLT6L3zATjs4k8jtzao6I0p/CgcDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:22:33.268934Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.05807","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:adba0426da812fc074f59463de0f71719387795b1c3495065262460386857350","sha256:48034ab29a6e476b3241b7db565d997244118d2747d94ec549d354ac2d8471d7"],"state_sha256":"d6cef3da126ab956ab4d11a7fa9450569ac160207d7ae272740cef8e87af38bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lx/Bv0h7ttZm5fyK/vld4QYiU6DCqkxhGOkfsRn0Muf3r1FWmPYtVVylM3dlcqgGlo4lEvpbPaHws7asMkrEBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T14:23:28.786339Z","bundle_sha256":"b52efe91f88215b9eba4be303f82ef0a559a91033d804634136dc4fffd2aca80"}}