{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DFOUPAIHZTPQHUZP24YIBRMNYZ","short_pith_number":"pith:DFOUPAIH","canonical_record":{"source":{"id":"2501.00170","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-30T22:47:32Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"e74a7919ad2ce9c7feb4623af4da4466e008e9868447a61bc213d2343831756f","abstract_canon_sha256":"94cb9d53ffabc28fbc25c71b2a001a29e478de7028705dcd8d676e355fee6442"},"schema_version":"1.0"},"canonical_sha256":"195d478107ccdf03d32fd73080c58dc65e22619d14a45cb73f6091e45c06a58b","source":{"kind":"arxiv","id":"2501.00170","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00170","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00170v1","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00170","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"DFOUPAIHZTPQ","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"DFOUPAIHZTPQHUZP","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"DFOUPAIH","created_at":"2026-07-05T09:56:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DFOUPAIHZTPQHUZP24YIBRMNYZ","target":"record","payload":{"canonical_record":{"source":{"id":"2501.00170","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-30T22:47:32Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"e74a7919ad2ce9c7feb4623af4da4466e008e9868447a61bc213d2343831756f","abstract_canon_sha256":"94cb9d53ffabc28fbc25c71b2a001a29e478de7028705dcd8d676e355fee6442"},"schema_version":"1.0"},"canonical_sha256":"195d478107ccdf03d32fd73080c58dc65e22619d14a45cb73f6091e45c06a58b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:56:05.417298Z","signature_b64":"McIcdGp44+O1VZMH4Ev3xtjWC+up7UBFiHUVMg2uQ68p9wL+KkA4VwZ/9cB12qArYhy75PElwLbEXd54DSWKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"195d478107ccdf03d32fd73080c58dc65e22619d14a45cb73f6091e45c06a58b","last_reissued_at":"2026-07-05T09:56:05.416793Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:56:05.416793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.00170","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":"2026-07-05T09:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NHCeod/tcdMP/dqJfFern7AaLHsOw0CEIMwRUJ8y9W+ZhoIeqns8P6ViXcAiKoWqj8WnysXpSYr6ofqrbh+QAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:40:09.788784Z"},"content_sha256":"e006d6e0740c28acbf3a2027e30fb3a52dc28f2fb9f1f005240a8afd8baa9747","schema_version":"1.0","event_id":"sha256:e006d6e0740c28acbf3a2027e30fb3a52dc28f2fb9f1f005240a8afd8baa9747"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DFOUPAIHZTPQHUZP24YIBRMNYZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Hongrui Shi, Po Yang, Valentin Radu","submitted_at":"2024-12-30T22:47:32Z","abstract_excerpt":"With the rapid expansion of edge devices, such as IoT devices, where crucial data needed for machine learning applications is generated, it becomes essential to promote their participation in privacy-preserving Federated Learning (FL) systems. The best way to achieve this desiderate is by reducing their training workload to match their constrained computational resources. While prior FL research has address the workload constrains by introducing lightweight models on the edge, limited attention has been given to optimizing on-device training efficiency through reducing the amount of data need "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00170","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/2501.00170/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":"2026-07-05T09:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/tTayCW8bBr24+SCL3x9ql2z2/kWd/HJM0YFucco+Pq9PuugQORRXVCrJk2kYOgbgoNzBvqwR4vaJ+CmA4JUAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:40:09.789163Z"},"content_sha256":"277ea0a12e30345971d88a0471e5a2a98dfc5ae2e9bf394bff646ea2a81abd57","schema_version":"1.0","event_id":"sha256:277ea0a12e30345971d88a0471e5a2a98dfc5ae2e9bf394bff646ea2a81abd57"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/bundle.json","state_url":"https://pith.science/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/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":"2026-07-06T09:40:09Z","links":{"resolver":"https://pith.science/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ","bundle":"https://pith.science/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/bundle.json","state":"https://pith.science/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DFOUPAIHZTPQHUZP24YIBRMNYZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DFOUPAIHZTPQHUZP24YIBRMNYZ","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":"94cb9d53ffabc28fbc25c71b2a001a29e478de7028705dcd8d676e355fee6442","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-30T22:47:32Z","title_canon_sha256":"e74a7919ad2ce9c7feb4623af4da4466e008e9868447a61bc213d2343831756f"},"schema_version":"1.0","source":{"id":"2501.00170","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00170","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00170v1","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00170","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"DFOUPAIHZTPQ","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"DFOUPAIHZTPQHUZP","created_at":"2026-07-05T09:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"DFOUPAIH","created_at":"2026-07-05T09:56:05Z"}],"graph_snapshots":[{"event_id":"sha256:277ea0a12e30345971d88a0471e5a2a98dfc5ae2e9bf394bff646ea2a81abd57","target":"graph","created_at":"2026-07-05T09:56:05Z","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/2501.00170/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid expansion of edge devices, such as IoT devices, where crucial data needed for machine learning applications is generated, it becomes essential to promote their participation in privacy-preserving Federated Learning (FL) systems. The best way to achieve this desiderate is by reducing their training workload to match their constrained computational resources. While prior FL research has address the workload constrains by introducing lightweight models on the edge, limited attention has been given to optimizing on-device training efficiency through reducing the amount of data need ","authors_text":"Hongrui Shi, Po Yang, Valentin Radu","cross_cats":["cs.AI","cs.DC"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-30T22:47:32Z","title":"Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00170","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:e006d6e0740c28acbf3a2027e30fb3a52dc28f2fb9f1f005240a8afd8baa9747","target":"record","created_at":"2026-07-05T09:56:05Z","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":"94cb9d53ffabc28fbc25c71b2a001a29e478de7028705dcd8d676e355fee6442","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-30T22:47:32Z","title_canon_sha256":"e74a7919ad2ce9c7feb4623af4da4466e008e9868447a61bc213d2343831756f"},"schema_version":"1.0","source":{"id":"2501.00170","kind":"arxiv","version":1}},"canonical_sha256":"195d478107ccdf03d32fd73080c58dc65e22619d14a45cb73f6091e45c06a58b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"195d478107ccdf03d32fd73080c58dc65e22619d14a45cb73f6091e45c06a58b","first_computed_at":"2026-07-05T09:56:05.416793Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:56:05.416793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"McIcdGp44+O1VZMH4Ev3xtjWC+up7UBFiHUVMg2uQ68p9wL+KkA4VwZ/9cB12qArYhy75PElwLbEXd54DSWKAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:56:05.417298Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.00170","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e006d6e0740c28acbf3a2027e30fb3a52dc28f2fb9f1f005240a8afd8baa9747","sha256:277ea0a12e30345971d88a0471e5a2a98dfc5ae2e9bf394bff646ea2a81abd57"],"state_sha256":"c74a58f01d8efdce54a4038422d4567f44877a0fb99df4a36bc73aae4a6ea951"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IDxADzk6t62bnV2Z9DGsb1PF+X30O2GuuAYdxCkDJfHbiR5g5WKe7s2Ok/oGbMaqgtQKnw1+Dr/dtZ3XaDKYAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T09:40:09.791677Z","bundle_sha256":"f0b333be11ab0d5d42e2ff5408caa394af267a4f7f7b238e521e5726db26fdc2"}}