{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WDD5LBUJEWC2UEKB5Y5CI2CDXV","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":"e2316860cf358b772fad211b1a1cee5064b23ad3b2e2788f44fb8be755f6d31a","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-07-21T09:17:12Z","title_canon_sha256":"5f1eea4aaf52b109cdfc59ccc8687c62b1066a46e025538aa4680f0c29dede1d"},"schema_version":"1.0","source":{"id":"2507.15416","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.15416","created_at":"2026-07-05T11:40:36Z"},{"alias_kind":"arxiv_version","alias_value":"2507.15416v1","created_at":"2026-07-05T11:40:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.15416","created_at":"2026-07-05T11:40:36Z"},{"alias_kind":"pith_short_12","alias_value":"WDD5LBUJEWC2","created_at":"2026-07-05T11:40:36Z"},{"alias_kind":"pith_short_16","alias_value":"WDD5LBUJEWC2UEKB","created_at":"2026-07-05T11:40:36Z"},{"alias_kind":"pith_short_8","alias_value":"WDD5LBUJ","created_at":"2026-07-05T11:40:36Z"}],"graph_snapshots":[{"event_id":"sha256:42fe932292fd6c6cdae1362da26e7a6f98528103dcf72928c744279598361b95","target":"graph","created_at":"2026-07-05T11:40:36Z","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/2507.15416/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"When the transferable set is unknowable, transfering informative knowledge as much as possible\\textemdash a principle we refer to as \\emph{sufficiency}, becomes crucial for enhancing transfer learning effectiveness. However, existing transfer learning methods not only overlook the sufficiency principle, but also rely on restrictive single-similarity assumptions (\\eg individual or combinatorial similarity), leading to suboptimal performance. To address these limitations, we propose a sufficiency-principled transfer learning framework via unified model averaging algorithms, accommodating both in","authors_text":"Huihang Liu, Xinyu Zhang, Xiyuan Zhang","cross_cats":["math.ST","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-07-21T09:17:12Z","title":"Sufficiency-principled Transfer Learning via Model Averaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.15416","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:a533caf040ca59a51d53c28b6ad52ecbf0a10c87a077089c538016ea93942628","target":"record","created_at":"2026-07-05T11:40:36Z","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":"e2316860cf358b772fad211b1a1cee5064b23ad3b2e2788f44fb8be755f6d31a","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-07-21T09:17:12Z","title_canon_sha256":"5f1eea4aaf52b109cdfc59ccc8687c62b1066a46e025538aa4680f0c29dede1d"},"schema_version":"1.0","source":{"id":"2507.15416","kind":"arxiv","version":1}},"canonical_sha256":"b0c7d586892585aa1141ee3a246843bd7a478c3fb0f1c71a3c81e9e2eff178f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0c7d586892585aa1141ee3a246843bd7a478c3fb0f1c71a3c81e9e2eff178f6","first_computed_at":"2026-07-05T11:40:36.788612Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:40:36.788612Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z8ubrtY/nUo96EqT86lzw3tWmIJLb+Pqmp3PL1dOMT8n0TSj/ahVcLNOk5vFQJ6A4E3kMSRxp//pHk/ggr4SCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:40:36.789293Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.15416","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a533caf040ca59a51d53c28b6ad52ecbf0a10c87a077089c538016ea93942628","sha256:42fe932292fd6c6cdae1362da26e7a6f98528103dcf72928c744279598361b95"],"state_sha256":"257c50cf4df55f13cacac088d8c65ff8b075b381ec531074d1c46573c4ac74c6"}