{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WFVHCD5U56O53O3BI3BODDCLZ6","short_pith_number":"pith:WFVHCD5U","schema_version":"1.0","canonical_sha256":"b16a710fb4ef9dddbb6146c2e18c4bcfa658040e6ea9a7f358d712166065dc01","source":{"kind":"arxiv","id":"2607.03763","version":1},"attestation_state":"computed","paper":{"title":"FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Haotian Mo, Hongyang Hu, Jiahuan Wang, Jie Liu, Ping Luo, Qinglin Wang, Qisong Xiao, Shuai Li, Tao Sun, Yigui Feng, Ziang Liu","submitted_at":"2026-07-04T08:31:49Z","abstract_excerpt":"Federated Transformer training increasingly relies on local AdamW, whose adaptive updates can provide much stronger local progress than SGD-based training. However, under heterogeneous client data, even globally corrected AdamW updates may remain highly uneven in coordinate-wise reliability. We refer to this phenomenon as coordinate trust mismatch. Existing federated adaptive optimizers mainly address mismatch at the client-update or communication-round level, but still apply the corrected adaptive direction densely and uniformly across coordinates. In this paper, we propose FedACT, a global-a"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.03763","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-04T08:31:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c45e2378ab90e5c565cd96a36ba4f99dc7da4e6174b6a654807c14a2892d7c12","abstract_canon_sha256":"ac0d0f4144540dd6931b6039951291cc28f673cfc4675dd6a09a498ff924ff0f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T02:18:06.376253Z","signature_b64":"WXCQkCdna/mfkdX0m270k1TXbi2ZYf+ZCFHVvexqLU+1O/EY5enA1Y1ZS32CAKDrBLWyM394+az2MWrvO8yJBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b16a710fb4ef9dddbb6146c2e18c4bcfa658040e6ea9a7f358d712166065dc01","last_reissued_at":"2026-07-07T02:18:06.375563Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T02:18:06.375563Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Haotian Mo, Hongyang Hu, Jiahuan Wang, Jie Liu, Ping Luo, Qinglin Wang, Qisong Xiao, Shuai Li, Tao Sun, Yigui Feng, Ziang Liu","submitted_at":"2026-07-04T08:31:49Z","abstract_excerpt":"Federated Transformer training increasingly relies on local AdamW, whose adaptive updates can provide much stronger local progress than SGD-based training. However, under heterogeneous client data, even globally corrected AdamW updates may remain highly uneven in coordinate-wise reliability. We refer to this phenomenon as coordinate trust mismatch. Existing federated adaptive optimizers mainly address mismatch at the client-update or communication-round level, but still apply the corrected adaptive direction densely and uniformly across coordinates. In this paper, we propose FedACT, a global-a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03763","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/2607.03763/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.03763","created_at":"2026-07-07T02:18:06.375674+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.03763v1","created_at":"2026-07-07T02:18:06.375674+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.03763","created_at":"2026-07-07T02:18:06.375674+00:00"},{"alias_kind":"pith_short_12","alias_value":"WFVHCD5U56O5","created_at":"2026-07-07T02:18:06.375674+00:00"},{"alias_kind":"pith_short_16","alias_value":"WFVHCD5U56O53O3B","created_at":"2026-07-07T02:18:06.375674+00:00"},{"alias_kind":"pith_short_8","alias_value":"WFVHCD5U","created_at":"2026-07-07T02:18:06.375674+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6","json":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6.json","graph_json":"https://pith.science/api/pith-number/WFVHCD5U56O53O3BI3BODDCLZ6/graph.json","events_json":"https://pith.science/api/pith-number/WFVHCD5U56O53O3BI3BODDCLZ6/events.json","paper":"https://pith.science/paper/WFVHCD5U"},"agent_actions":{"view_html":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6","download_json":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6.json","view_paper":"https://pith.science/paper/WFVHCD5U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.03763&json=true","fetch_graph":"https://pith.science/api/pith-number/WFVHCD5U56O53O3BI3BODDCLZ6/graph.json","fetch_events":"https://pith.science/api/pith-number/WFVHCD5U56O53O3BI3BODDCLZ6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6/action/storage_attestation","attest_author":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6/action/author_attestation","sign_citation":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6/action/citation_signature","submit_replication":"https://pith.science/pith/WFVHCD5U56O53O3BI3BODDCLZ6/action/replication_record"}},"created_at":"2026-07-07T02:18:06.375674+00:00","updated_at":"2026-07-07T02:18:06.375674+00:00"}