{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VJVXNYRZUBOQIHTIZZTYYEWERQ","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":"f7f6c79a0915eb379cd2bf35daee8f189263056a64bda04a457d78ad58148bbe","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T14:22:56Z","title_canon_sha256":"56b357dd68ae610a2b00cc25b51ca5a7cf4b70daf922f8f2ad40b2a9bf74526c"},"schema_version":"1.0","source":{"id":"2502.04959","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.04959","created_at":"2026-07-05T11:19:51Z"},{"alias_kind":"arxiv_version","alias_value":"2502.04959v3","created_at":"2026-07-05T11:19:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.04959","created_at":"2026-07-05T11:19:51Z"},{"alias_kind":"pith_short_12","alias_value":"VJVXNYRZUBOQ","created_at":"2026-07-05T11:19:51Z"},{"alias_kind":"pith_short_16","alias_value":"VJVXNYRZUBOQIHTI","created_at":"2026-07-05T11:19:51Z"},{"alias_kind":"pith_short_8","alias_value":"VJVXNYRZ","created_at":"2026-07-05T11:19:51Z"}],"graph_snapshots":[{"event_id":"sha256:eaa8f91382ea49c753ddf2af909c0133eb041ed63e4c0d6baf6615b841603d8a","target":"graph","created_at":"2026-07-05T11:19:51Z","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/2502.04959/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model merging integrates the weights of multiple task-specific models into a single multi-task model. Despite recent interest in the problem, a significant performance gap between the combined and single-task models remains. In this paper, we investigate the key characteristics of task matrices -- weight update matrices applied to a pre-trained model -- that enable effective merging. We show that alignment between singular components of task-specific and merged matrices strongly correlates with performance improvement over the pre-trained model. Based on this, we propose an isotropic merging f","authors_text":"Andrew D. Bagdanov, Bart{\\l}omiej Twardowski, Daniel Marczak, Joost Van De Weijer, Sebastian Cygert, Simone Magistri","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T14:22:56Z","title":"No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.04959","kind":"arxiv","version":3},"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":"sha256:5018a37b59e19a18578edf1411693d31d9280d261d592d2afdd2a24d13f211af","target":"record","created_at":"2026-07-05T11:19:51Z","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":"f7f6c79a0915eb379cd2bf35daee8f189263056a64bda04a457d78ad58148bbe","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T14:22:56Z","title_canon_sha256":"56b357dd68ae610a2b00cc25b51ca5a7cf4b70daf922f8f2ad40b2a9bf74526c"},"schema_version":"1.0","source":{"id":"2502.04959","kind":"arxiv","version":3}},"canonical_sha256":"aa6b76e239a05d041e68ce678c12c48c1e5b965e45654d4b68aeb4f68fb0bb1e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa6b76e239a05d041e68ce678c12c48c1e5b965e45654d4b68aeb4f68fb0bb1e","first_computed_at":"2026-07-05T11:19:51.173472Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:19:51.173472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IMtLJQkwuCk1e81YJoJuCk5IppYhE7mYpWRt4RwzMnTohJSvsoCBGJx7YRM6Nnj0KRWCm6n22SKp/M9ZERmJBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:19:51.173970Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.04959","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5018a37b59e19a18578edf1411693d31d9280d261d592d2afdd2a24d13f211af","sha256:eaa8f91382ea49c753ddf2af909c0133eb041ed63e4c0d6baf6615b841603d8a"],"state_sha256":"3355dcca3ec196e47645d88e0fd0cf2b57b0dc5a1505b37008c527580f8a5377"}