{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:LH3QEX5ZSH7XCL6VIZRRRK3YVI","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":"6b506549394f0d41f20a3ebf05ca63cc9240a1a3febf7a5fd4cad9efa79e926a","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-18T02:26:38Z","title_canon_sha256":"42d9e734fbca454867dc305086fc405779befcc359dae52661ce0080a8473f2d"},"schema_version":"1.0","source":{"id":"2112.09824","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.09824","created_at":"2026-07-05T03:42:07Z"},{"alias_kind":"arxiv_version","alias_value":"2112.09824v1","created_at":"2026-07-05T03:42:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.09824","created_at":"2026-07-05T03:42:07Z"},{"alias_kind":"pith_short_12","alias_value":"LH3QEX5ZSH7X","created_at":"2026-07-05T03:42:07Z"},{"alias_kind":"pith_short_16","alias_value":"LH3QEX5ZSH7XCL6V","created_at":"2026-07-05T03:42:07Z"},{"alias_kind":"pith_short_8","alias_value":"LH3QEX5Z","created_at":"2026-07-05T03:42:07Z"}],"graph_snapshots":[{"event_id":"sha256:349ea353f02263d856cc4b45dcc5a230e7b4b5d847a3aa4dad8a70797d1a8373","target":"graph","created_at":"2026-07-05T03:42:07Z","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/2112.09824/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) enables distribution of machine learning workloads from the cloud to resource-limited edge devices. Unfortunately, current deep networks remain not only too compute-heavy for inference and training on edge devices, but also too large for communicating updates over bandwidth-constrained networks. In this paper, we develop, implement, and experimentally validate a novel FL framework termed Federated Dynamic Sparse Training (FedDST) by which complex neural networks can be deployed and trained with substantially improved efficiency in both on-device computation and in-netwo","authors_text":"Haris Vikalo, Sameer Bibikar, Xiaohan Chen, Zhangyang Wang","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-18T02:26:38Z","title":"Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.09824","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":"sha256:69e1f099d07b0425db5a0d34374d5d79352ca7facbd4b7c211cd52e03a287d1d","target":"record","created_at":"2026-07-05T03:42:07Z","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":"6b506549394f0d41f20a3ebf05ca63cc9240a1a3febf7a5fd4cad9efa79e926a","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-18T02:26:38Z","title_canon_sha256":"42d9e734fbca454867dc305086fc405779befcc359dae52661ce0080a8473f2d"},"schema_version":"1.0","source":{"id":"2112.09824","kind":"arxiv","version":1}},"canonical_sha256":"59f7025fb991ff712fd5466318ab78aa19db64a97ed29153e75ad0b166cab1e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59f7025fb991ff712fd5466318ab78aa19db64a97ed29153e75ad0b166cab1e3","first_computed_at":"2026-07-05T03:42:07.308912Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:42:07.308912Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dBZznoCAv/rKKFKX1Xq4Y+5xYCwx+3kZQGGrl591+Pld3xsGKVwYifjARwK4dfE866RoeWFU+j8LORSEJys3Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T03:42:07.309465Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.09824","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69e1f099d07b0425db5a0d34374d5d79352ca7facbd4b7c211cd52e03a287d1d","sha256:349ea353f02263d856cc4b45dcc5a230e7b4b5d847a3aa4dad8a70797d1a8373"],"state_sha256":"1a92d457b18e8714a203d46d8db0f26c94c66b5130cba8bd63f5ab5cf1b17fab"}