{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:L2LGSYQBWK2XTGLQ7DWQEEGVEN","short_pith_number":"pith:L2LGSYQB","canonical_record":{"source":{"id":"2412.19989","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-28T03:20:36Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"21855daf1cbaeac0ace7ea124929769cee8b991f7415045b3e65a2f828bef5aa","abstract_canon_sha256":"19093ee48c3640ac0fb35d4d66757236b28e5f2814704e9a0b905003099cea5e"},"schema_version":"1.0"},"canonical_sha256":"5e96696201b2b5799970f8ed0210d5236bd3661c9a4d5403e6509dbedb1e7d91","source":{"kind":"arxiv","id":"2412.19989","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.19989","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"arxiv_version","alias_value":"2412.19989v1","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19989","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_12","alias_value":"L2LGSYQBWK2X","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_16","alias_value":"L2LGSYQBWK2XTGLQ","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_8","alias_value":"L2LGSYQB","created_at":"2026-07-05T09:54:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:L2LGSYQBWK2XTGLQ7DWQEEGVEN","target":"record","payload":{"canonical_record":{"source":{"id":"2412.19989","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-28T03:20:36Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"21855daf1cbaeac0ace7ea124929769cee8b991f7415045b3e65a2f828bef5aa","abstract_canon_sha256":"19093ee48c3640ac0fb35d4d66757236b28e5f2814704e9a0b905003099cea5e"},"schema_version":"1.0"},"canonical_sha256":"5e96696201b2b5799970f8ed0210d5236bd3661c9a4d5403e6509dbedb1e7d91","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:52.805632Z","signature_b64":"fA7tmwdUXQXRXyO6Um5mHNJ8NneZlZN0PwnXvpjEFyhb2DdJOIsuhIsL9hYdQPfSGe65NKGUMROG/Q+9QPHGAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e96696201b2b5799970f8ed0210d5236bd3661c9a4d5403e6509dbedb1e7d91","last_reissued_at":"2026-07-05T09:54:52.805159Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:52.805159Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.19989","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":"2026-07-05T09:54:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OzVBe8yGJLY9keK2kHIYjhEGcOB8L52GRIc8BRsU0TdOQZk34Ab5hDWew3Ur8MT86ydNGtqAEB3mezv5ucEgDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:45:02.531061Z"},"content_sha256":"cbac41c787262866baa331cce90678360460cabd469b35d43701025302514e40","schema_version":"1.0","event_id":"sha256:cbac41c787262866baa331cce90678360460cabd469b35d43701025302514e40"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:L2LGSYQBWK2XTGLQ7DWQEEGVEN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Caesar: A Low-deviation Compression Approach for Efficient Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.LG","authors_text":"Hongli Xu, Jiaming Yan, Jianchun Liu, Jiantao Gong, Kun Hou, Liusheng Huang, Xudong Liu","submitted_at":"2024-12-28T03:20:36Z","abstract_excerpt":"Compression is an efficient way to relieve the tremendous communication overhead of federated learning (FL) systems. However, for the existing works, the information loss under compression will lead to unexpected model/gradient deviation for the FL training, significantly degrading the training performance, especially under the challenges of data heterogeneity and model obsolescence. To strike a delicate trade-off between model accuracy and traffic cost, we propose Caesar, a novel FL framework with a low-deviation compression approach. For the global model download, we design a greedy method t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19989","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/2412.19989/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":"2026-07-05T09:54:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7mhrh55A3/lboDYlQeIB60IydBgwtTEHHp2fT1K/E0FSfGXywjbca8UicY6VBMocSN+d7aO6B2TrogSVlG2bBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:45:02.531674Z"},"content_sha256":"fb3279c75be5caf64e0fc33793988a4d3576bca98918b94131fbb1e4a64e5068","schema_version":"1.0","event_id":"sha256:fb3279c75be5caf64e0fc33793988a4d3576bca98918b94131fbb1e4a64e5068"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/bundle.json","state_url":"https://pith.science/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/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":"2026-08-20T13:45:02Z","links":{"resolver":"https://pith.science/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN","bundle":"https://pith.science/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/bundle.json","state":"https://pith.science/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L2LGSYQBWK2XTGLQ7DWQEEGVEN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:L2LGSYQBWK2XTGLQ7DWQEEGVEN","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":"19093ee48c3640ac0fb35d4d66757236b28e5f2814704e9a0b905003099cea5e","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-28T03:20:36Z","title_canon_sha256":"21855daf1cbaeac0ace7ea124929769cee8b991f7415045b3e65a2f828bef5aa"},"schema_version":"1.0","source":{"id":"2412.19989","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.19989","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"arxiv_version","alias_value":"2412.19989v1","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19989","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_12","alias_value":"L2LGSYQBWK2X","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_16","alias_value":"L2LGSYQBWK2XTGLQ","created_at":"2026-07-05T09:54:52Z"},{"alias_kind":"pith_short_8","alias_value":"L2LGSYQB","created_at":"2026-07-05T09:54:52Z"}],"graph_snapshots":[{"event_id":"sha256:fb3279c75be5caf64e0fc33793988a4d3576bca98918b94131fbb1e4a64e5068","target":"graph","created_at":"2026-07-05T09:54:52Z","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/2412.19989/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Compression is an efficient way to relieve the tremendous communication overhead of federated learning (FL) systems. However, for the existing works, the information loss under compression will lead to unexpected model/gradient deviation for the FL training, significantly degrading the training performance, especially under the challenges of data heterogeneity and model obsolescence. To strike a delicate trade-off between model accuracy and traffic cost, we propose Caesar, a novel FL framework with a low-deviation compression approach. For the global model download, we design a greedy method t","authors_text":"Hongli Xu, Jiaming Yan, Jianchun Liu, Jiantao Gong, Kun Hou, Liusheng Huang, Xudong Liu","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-28T03:20:36Z","title":"Caesar: A Low-deviation Compression Approach for Efficient Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19989","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:cbac41c787262866baa331cce90678360460cabd469b35d43701025302514e40","target":"record","created_at":"2026-07-05T09:54:52Z","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":"19093ee48c3640ac0fb35d4d66757236b28e5f2814704e9a0b905003099cea5e","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-28T03:20:36Z","title_canon_sha256":"21855daf1cbaeac0ace7ea124929769cee8b991f7415045b3e65a2f828bef5aa"},"schema_version":"1.0","source":{"id":"2412.19989","kind":"arxiv","version":1}},"canonical_sha256":"5e96696201b2b5799970f8ed0210d5236bd3661c9a4d5403e6509dbedb1e7d91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e96696201b2b5799970f8ed0210d5236bd3661c9a4d5403e6509dbedb1e7d91","first_computed_at":"2026-07-05T09:54:52.805159Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:52.805159Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fA7tmwdUXQXRXyO6Um5mHNJ8NneZlZN0PwnXvpjEFyhb2DdJOIsuhIsL9hYdQPfSGe65NKGUMROG/Q+9QPHGAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:52.805632Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.19989","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbac41c787262866baa331cce90678360460cabd469b35d43701025302514e40","sha256:fb3279c75be5caf64e0fc33793988a4d3576bca98918b94131fbb1e4a64e5068"],"state_sha256":"2ee0dd74d3209cd1b5e4cfbca4c269ae7bfcb85da23265cc95fd365c3ca84d07"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vxVSuM/bFeOiZBkZna7tabQwhrx0MS7xVZorWeGY3IfZGGh9n7ykvJH087YAPbpqQjJcXZ3fKNnwu4ggGROzAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T13:45:02.536506Z","bundle_sha256":"c2920c3eb185f9a00977474cb92edb23c3d27853e82d6b2418dd99dc49433292"}}