{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:MBMLJIYXIGCK4WBBCZLKMXLYNI","short_pith_number":"pith:MBMLJIYX","canonical_record":{"source":{"id":"2310.03163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-04T21:11:40Z","cross_cats_sorted":[],"title_canon_sha256":"770b3fc0fc481e0013baff0952c99d73dfc73067df90ed9a7a397995ca3d8087","abstract_canon_sha256":"02400d4dc9194e211cf2bf4435a74a4ce758fe07201a13c54e1aa165ac826fa4"},"schema_version":"1.0"},"canonical_sha256":"6058b4a3174184ae58211656a65d786a2e19ff30b2fbdc17224bad5d164e4d67","source":{"kind":"arxiv","id":"2310.03163","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03163","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03163v1","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03163","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_12","alias_value":"MBMLJIYXIGCK","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_16","alias_value":"MBMLJIYXIGCK4WBB","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_8","alias_value":"MBMLJIYX","created_at":"2026-07-05T07:45:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:MBMLJIYXIGCK4WBBCZLKMXLYNI","target":"record","payload":{"canonical_record":{"source":{"id":"2310.03163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-04T21:11:40Z","cross_cats_sorted":[],"title_canon_sha256":"770b3fc0fc481e0013baff0952c99d73dfc73067df90ed9a7a397995ca3d8087","abstract_canon_sha256":"02400d4dc9194e211cf2bf4435a74a4ce758fe07201a13c54e1aa165ac826fa4"},"schema_version":"1.0"},"canonical_sha256":"6058b4a3174184ae58211656a65d786a2e19ff30b2fbdc17224bad5d164e4d67","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:45:49.241433Z","signature_b64":"DqCQlLRc0TIf34PTkFhSrFrJeKEamqggKmLMXhpiP0YONZVBJ8CmupJ3D8lx36yYWbW4fauK4Kgs+Ht2DkFWBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6058b4a3174184ae58211656a65d786a2e19ff30b2fbdc17224bad5d164e4d67","last_reissued_at":"2026-07-05T07:45:49.240981Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:45:49.240981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.03163","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":"2026-07-05T07:45:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VzX8QuuupRugTMcKZyKT1llVApLUdbtWe0uviElM17BNWOES0CYBTvshi+YgX9TbhWESXbJaHPcEQlDXmD/PBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T21:35:21.677005Z"},"content_sha256":"461e294bbab8a6caec08d6bedf6962b1140f61dae27e4a3758a76c54426ff7be","schema_version":"1.0","event_id":"sha256:461e294bbab8a6caec08d6bedf6962b1140f61dae27e4a3758a76c54426ff7be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:MBMLJIYXIGCK4WBBCZLKMXLYNI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FedNAR: Federated Optimization with Normalized Annealing Regularization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ang Li, Chong Tian, Eric P. Xing, Hongyi Wang, Junbo Li, Qirong Ho","submitted_at":"2023-10-04T21:11:40Z","abstract_excerpt":"Weight decay is a standard technique to improve generalization performance in modern deep neural network optimization, and is also widely adopted in federated learning (FL) to prevent overfitting in local clients. In this paper, we first explore the choices of weight decay and identify that weight decay value appreciably influences the convergence of existing FL algorithms. While preventing overfitting is crucial, weight decay can introduce a different optimization goal towards the global objective, which is further amplified in FL due to multiple local updates and heterogeneous data distribut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03163","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/2310.03163/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":"2026-07-05T07:45:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FK7NimaMW2k0Y+hwI913bH2WNx/1mDB+Ilyd+SxVdV1fW9peAioOXAljC9zzjjtN2DcGJRkq63Bw+ttcAt5RAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T21:35:21.677584Z"},"content_sha256":"819f1b44fcf0d1c2c0ac63a723bb246634e078c4cfba0259083c130239fa8c95","schema_version":"1.0","event_id":"sha256:819f1b44fcf0d1c2c0ac63a723bb246634e078c4cfba0259083c130239fa8c95"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/bundle.json","state_url":"https://pith.science/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/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":"2026-08-06T21:35:21Z","links":{"resolver":"https://pith.science/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI","bundle":"https://pith.science/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/bundle.json","state":"https://pith.science/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MBMLJIYXIGCK4WBBCZLKMXLYNI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MBMLJIYXIGCK4WBBCZLKMXLYNI","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":"02400d4dc9194e211cf2bf4435a74a4ce758fe07201a13c54e1aa165ac826fa4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-04T21:11:40Z","title_canon_sha256":"770b3fc0fc481e0013baff0952c99d73dfc73067df90ed9a7a397995ca3d8087"},"schema_version":"1.0","source":{"id":"2310.03163","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03163","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03163v1","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03163","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_12","alias_value":"MBMLJIYXIGCK","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_16","alias_value":"MBMLJIYXIGCK4WBB","created_at":"2026-07-05T07:45:49Z"},{"alias_kind":"pith_short_8","alias_value":"MBMLJIYX","created_at":"2026-07-05T07:45:49Z"}],"graph_snapshots":[{"event_id":"sha256:819f1b44fcf0d1c2c0ac63a723bb246634e078c4cfba0259083c130239fa8c95","target":"graph","created_at":"2026-07-05T07:45:49Z","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/2310.03163/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Weight decay is a standard technique to improve generalization performance in modern deep neural network optimization, and is also widely adopted in federated learning (FL) to prevent overfitting in local clients. In this paper, we first explore the choices of weight decay and identify that weight decay value appreciably influences the convergence of existing FL algorithms. While preventing overfitting is crucial, weight decay can introduce a different optimization goal towards the global objective, which is further amplified in FL due to multiple local updates and heterogeneous data distribut","authors_text":"Ang Li, Chong Tian, Eric P. Xing, Hongyi Wang, Junbo Li, Qirong Ho","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-04T21:11:40Z","title":"FedNAR: Federated Optimization with Normalized Annealing Regularization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03163","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":"sha256:461e294bbab8a6caec08d6bedf6962b1140f61dae27e4a3758a76c54426ff7be","target":"record","created_at":"2026-07-05T07:45:49Z","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":"02400d4dc9194e211cf2bf4435a74a4ce758fe07201a13c54e1aa165ac826fa4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-04T21:11:40Z","title_canon_sha256":"770b3fc0fc481e0013baff0952c99d73dfc73067df90ed9a7a397995ca3d8087"},"schema_version":"1.0","source":{"id":"2310.03163","kind":"arxiv","version":1}},"canonical_sha256":"6058b4a3174184ae58211656a65d786a2e19ff30b2fbdc17224bad5d164e4d67","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6058b4a3174184ae58211656a65d786a2e19ff30b2fbdc17224bad5d164e4d67","first_computed_at":"2026-07-05T07:45:49.240981Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:45:49.240981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DqCQlLRc0TIf34PTkFhSrFrJeKEamqggKmLMXhpiP0YONZVBJ8CmupJ3D8lx36yYWbW4fauK4Kgs+Ht2DkFWBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:45:49.241433Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.03163","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:461e294bbab8a6caec08d6bedf6962b1140f61dae27e4a3758a76c54426ff7be","sha256:819f1b44fcf0d1c2c0ac63a723bb246634e078c4cfba0259083c130239fa8c95"],"state_sha256":"4d540690faabfa54e93c66e4af8801998f0f47d5856f4b5bb87d3156c89c3e4c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z5iXho7xWBRwb8USLk2lbGTpvUAft8TcEbL9rlwylMmT9HTbj8XtI8COJj32BH10INpaJaQC//4WSut8PZtwBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T21:35:21.683448Z","bundle_sha256":"8384fea384aab5f7474f47ea09e388e48db1fcb5328240f73043ed30529f4f5e"}}