{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TUWEVFC5NRTKNAT3256DBEA5JH","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":"c0695949309d81c0bea803536ea1fa8b7bc952f59913a7b031e04007959ad2ab","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-07-24T01:55:15Z","title_canon_sha256":"7c5cf480e987d1b053dceeea4f7338263d9786d4434a5b627bbd0f7c0be6a804"},"schema_version":"1.0","source":{"id":"2507.18025","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.18025","created_at":"2026-07-05T11:42:39Z"},{"alias_kind":"arxiv_version","alias_value":"2507.18025v1","created_at":"2026-07-05T11:42:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18025","created_at":"2026-07-05T11:42:39Z"},{"alias_kind":"pith_short_12","alias_value":"TUWEVFC5NRTK","created_at":"2026-07-05T11:42:39Z"},{"alias_kind":"pith_short_16","alias_value":"TUWEVFC5NRTKNAT3","created_at":"2026-07-05T11:42:39Z"},{"alias_kind":"pith_short_8","alias_value":"TUWEVFC5","created_at":"2026-07-05T11:42:39Z"}],"graph_snapshots":[{"event_id":"sha256:41dd9c8fc0fff18330432dae996684f8ed3c1118d5baed9d84cccdbe8d9a91a3","target":"graph","created_at":"2026-07-05T11:42:39Z","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/2507.18025/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed multi-task learning (DMTL) effectively improves model generalization performance through the collaborative training of multiple related models. However, in large-scale learning scenarios, communication bottlenecks severely limit practical system performance. In this paper, we investigate the communication bottleneck within a typical DMTL system that employs non-linear global updates. This system involves distributed workers, assisted by a central server, who collaboratively learn distinct models derived from a non-linear aggregation of their local model parameters. We first charact","authors_text":"Lingyu Zhang, Minquan Cheng, Yongkang Wang, Youlong Wu","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-07-24T01:55:15Z","title":"A Novel Coded Computing Approach for Distributed Multi-Task Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18025","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":"sha256:637d783d0369dd16547eb9c0288a722c024b0fb1599162d154d13ee5ade51ab3","target":"record","created_at":"2026-07-05T11:42:39Z","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":"c0695949309d81c0bea803536ea1fa8b7bc952f59913a7b031e04007959ad2ab","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-07-24T01:55:15Z","title_canon_sha256":"7c5cf480e987d1b053dceeea4f7338263d9786d4434a5b627bbd0f7c0be6a804"},"schema_version":"1.0","source":{"id":"2507.18025","kind":"arxiv","version":1}},"canonical_sha256":"9d2c4a945d6c66a6827bd77c30901d49d6e682f77665542deddf9e9f657d9e6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d2c4a945d6c66a6827bd77c30901d49d6e682f77665542deddf9e9f657d9e6e","first_computed_at":"2026-07-05T11:42:39.576971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:42:39.576971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vrLRmNijL1nOcslY1pUnurP4xoTWUfj2I/TUgAzznbn/dozB3TFsdmekDwb6+6/YPIcd8XFJIPoR/sf/YlRzCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:42:39.577444Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.18025","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:637d783d0369dd16547eb9c0288a722c024b0fb1599162d154d13ee5ade51ab3","sha256:41dd9c8fc0fff18330432dae996684f8ed3c1118d5baed9d84cccdbe8d9a91a3"],"state_sha256":"dec80aa11571a6523cb9ed6e65df48d28bd3a444122e4d91693c97088760c9eb"}