{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:35OYTPVRVBIYIFFLMG54CLXYBD","short_pith_number":"pith:35OYTPVR","canonical_record":{"source":{"id":"2311.06879","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T15:43:39Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"b0ad0e8d5a2a4b309dfac69f7605faf2333c71b22e78a655504096a5ea00c44e","abstract_canon_sha256":"1a777d134b7a11b719e749f6d08b7ccef34a3b0243e724f13a905a8a4d80060e"},"schema_version":"1.0"},"canonical_sha256":"df5d89beb1a8518414ab61bbc12ef808d684e4ca141246111d940f88fde8b664","source":{"kind":"arxiv","id":"2311.06879","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06879","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06879v1","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06879","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_12","alias_value":"35OYTPVRVBIY","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_16","alias_value":"35OYTPVRVBIYIFFL","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_8","alias_value":"35OYTPVR","created_at":"2026-07-05T07:12:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:35OYTPVRVBIYIFFLMG54CLXYBD","target":"record","payload":{"canonical_record":{"source":{"id":"2311.06879","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T15:43:39Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"b0ad0e8d5a2a4b309dfac69f7605faf2333c71b22e78a655504096a5ea00c44e","abstract_canon_sha256":"1a777d134b7a11b719e749f6d08b7ccef34a3b0243e724f13a905a8a4d80060e"},"schema_version":"1.0"},"canonical_sha256":"df5d89beb1a8518414ab61bbc12ef808d684e4ca141246111d940f88fde8b664","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:12:05.053914Z","signature_b64":"NuxcJy/aECg9Lz72X/6i4ZKizwzR//eBd3UwC/ODPZ0Anf+hh91rl7Oj8qN++E2P54EPVqtJCY1g/pSSdvQVAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df5d89beb1a8518414ab61bbc12ef808d684e4ca141246111d940f88fde8b664","last_reissued_at":"2026-07-05T07:12:05.053438Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:12:05.053438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.06879","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":"2026-07-05T07:12:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"arY9gw6h1dDFaoujP06um7gZoWW+aFrBuIlxhQPHe3BfNd+nvgGvJfxJqj2GEw0QjIc0iLaCqwR5ZYDXKDTCBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:30:25.384643Z"},"content_sha256":"69d29d118c570c4225a684e618558d3d25dbf3c840d78559a6229420ec8a4d90","schema_version":"1.0","event_id":"sha256:69d29d118c570c4225a684e618558d3d25dbf3c840d78559a6229420ec8a4d90"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:35OYTPVRVBIYIFFLMG54CLXYBD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.LG","authors_text":"Gang Wang, Han Yu, Liping Yi, Xiaoguang Liu","submitted_at":"2023-11-12T15:43:39Z","abstract_excerpt":"As a privacy-preserving collaborative machine learning paradigm, federated learning (FL) has attracted significant interest from academia and the industry alike. To allow each data owner (a.k.a., FL clients) to train a heterogeneous and personalized local model based on its local data distribution, system resources and requirements on model structure, the field of model-heterogeneous personalized federated learning (MHPFL) has emerged. Existing MHPFL approaches either rely on the availability of a public dataset with special characteristics to facilitate knowledge transfer, incur high computat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06879","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/2311.06879/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":"2026-07-05T07:12:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1on04GIcx4lAfG8NyFYfH2pmyEGahCnibL4phE2tQS+nXFeDwPzaK17X34+1jbLitCBciynWFVSLH7lKw6U6Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:30:25.385017Z"},"content_sha256":"92682ced775d36176396b30e3024a87b410820ceb89ee0a471a332e68e97e31c","schema_version":"1.0","event_id":"sha256:92682ced775d36176396b30e3024a87b410820ceb89ee0a471a332e68e97e31c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/35OYTPVRVBIYIFFLMG54CLXYBD/bundle.json","state_url":"https://pith.science/pith/35OYTPVRVBIYIFFLMG54CLXYBD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/35OYTPVRVBIYIFFLMG54CLXYBD/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":"2026-08-07T22:30:25Z","links":{"resolver":"https://pith.science/pith/35OYTPVRVBIYIFFLMG54CLXYBD","bundle":"https://pith.science/pith/35OYTPVRVBIYIFFLMG54CLXYBD/bundle.json","state":"https://pith.science/pith/35OYTPVRVBIYIFFLMG54CLXYBD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/35OYTPVRVBIYIFFLMG54CLXYBD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:35OYTPVRVBIYIFFLMG54CLXYBD","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":"1a777d134b7a11b719e749f6d08b7ccef34a3b0243e724f13a905a8a4d80060e","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T15:43:39Z","title_canon_sha256":"b0ad0e8d5a2a4b309dfac69f7605faf2333c71b22e78a655504096a5ea00c44e"},"schema_version":"1.0","source":{"id":"2311.06879","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06879","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06879v1","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06879","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_12","alias_value":"35OYTPVRVBIY","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_16","alias_value":"35OYTPVRVBIYIFFL","created_at":"2026-07-05T07:12:05Z"},{"alias_kind":"pith_short_8","alias_value":"35OYTPVR","created_at":"2026-07-05T07:12:05Z"}],"graph_snapshots":[{"event_id":"sha256:92682ced775d36176396b30e3024a87b410820ceb89ee0a471a332e68e97e31c","target":"graph","created_at":"2026-07-05T07:12:05Z","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/2311.06879/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As a privacy-preserving collaborative machine learning paradigm, federated learning (FL) has attracted significant interest from academia and the industry alike. To allow each data owner (a.k.a., FL clients) to train a heterogeneous and personalized local model based on its local data distribution, system resources and requirements on model structure, the field of model-heterogeneous personalized federated learning (MHPFL) has emerged. Existing MHPFL approaches either rely on the availability of a public dataset with special characteristics to facilitate knowledge transfer, incur high computat","authors_text":"Gang Wang, Han Yu, Liping Yi, Xiaoguang Liu","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T15:43:39Z","title":"pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06879","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":"sha256:69d29d118c570c4225a684e618558d3d25dbf3c840d78559a6229420ec8a4d90","target":"record","created_at":"2026-07-05T07:12:05Z","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":"1a777d134b7a11b719e749f6d08b7ccef34a3b0243e724f13a905a8a4d80060e","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T15:43:39Z","title_canon_sha256":"b0ad0e8d5a2a4b309dfac69f7605faf2333c71b22e78a655504096a5ea00c44e"},"schema_version":"1.0","source":{"id":"2311.06879","kind":"arxiv","version":1}},"canonical_sha256":"df5d89beb1a8518414ab61bbc12ef808d684e4ca141246111d940f88fde8b664","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df5d89beb1a8518414ab61bbc12ef808d684e4ca141246111d940f88fde8b664","first_computed_at":"2026-07-05T07:12:05.053438Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:12:05.053438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NuxcJy/aECg9Lz72X/6i4ZKizwzR//eBd3UwC/ODPZ0Anf+hh91rl7Oj8qN++E2P54EPVqtJCY1g/pSSdvQVAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:12:05.053914Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.06879","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69d29d118c570c4225a684e618558d3d25dbf3c840d78559a6229420ec8a4d90","sha256:92682ced775d36176396b30e3024a87b410820ceb89ee0a471a332e68e97e31c"],"state_sha256":"450cc99b9d933a35d70478a8c9ec546dbb851d5aa2d93cfa28a0f0f734d1ac64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QTkna45MU+q+un7dnSAfiVRezIpw2W+lk/DKlq1z81Hdn27s9H9p443Xvcg5CoD6dRWEDob/ph65EAH026icCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T22:30:25.387790Z","bundle_sha256":"dcfea63450e50f5cb2b08965fd836b3dbe30c34fc227625714874d8d9e71f303"}}