{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DMEKZWWHXG2DO2OKA2UO62W4QY","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":"adca7473bc3e8e5cebe30cb216f5c2fdfe6ad562946835fdb82790054565fab6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T14:04:48Z","title_canon_sha256":"fa5ca46ad160f0a748bdd158e9d3f248418e12c2ad46da4cc62fea2ca2920d16"},"schema_version":"1.0","source":{"id":"2607.24465","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.24465","created_at":"2026-07-28T02:24:05Z"},{"alias_kind":"arxiv_version","alias_value":"2607.24465v1","created_at":"2026-07-28T02:24:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.24465","created_at":"2026-07-28T02:24:05Z"},{"alias_kind":"pith_short_12","alias_value":"DMEKZWWHXG2D","created_at":"2026-07-28T02:24:05Z"},{"alias_kind":"pith_short_16","alias_value":"DMEKZWWHXG2DO2OK","created_at":"2026-07-28T02:24:05Z"},{"alias_kind":"pith_short_8","alias_value":"DMEKZWWH","created_at":"2026-07-28T02:24:05Z"}],"graph_snapshots":[{"event_id":"sha256:f7c2b0ba81f99d63913f1ed9ebf35a471d6bbc1302b3525b1c59bd0c5291c5d5","target":"graph","created_at":"2026-07-28T02:24:05Z","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/2607.24465/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model merging aims to combine multiple domain-specialized experts trained from a shared foundation model into a single multi-task model. Existing approaches largely focus on improving the merging procedure itself and typically assume experts obtained through full-parameter fine-tuning. In this work, we revisit expert training for model merging. We first show that prompt-based adaptation provides a strong baseline: independently learned prompts can be exploited across tasks while keeping the backbone fixed, avoiding the interference introduced by weight merging. Building on this observation, we","authors_text":"Aniello Panariello, Christos Georgakilas, Dimosthenis Karatzas, Joost Van De Weijer, Samir El Karrat Moreno, Simone Calderara","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T14:04:48Z","title":"Rethinking Expert Training for Model Merging with Prompt Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.24465","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":"sha256:9a0a7b15dc3b0f695fc7abb2b6aa5fd86bc2b5722a155cb109f8b91d89972b75","target":"record","created_at":"2026-07-28T02:24:05Z","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":"adca7473bc3e8e5cebe30cb216f5c2fdfe6ad562946835fdb82790054565fab6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T14:04:48Z","title_canon_sha256":"fa5ca46ad160f0a748bdd158e9d3f248418e12c2ad46da4cc62fea2ca2920d16"},"schema_version":"1.0","source":{"id":"2607.24465","kind":"arxiv","version":1}},"canonical_sha256":"1b08acdac7b9b43769ca06a8ef6adc8606c1618340e0bd767c5abebe7f1b2ee0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b08acdac7b9b43769ca06a8ef6adc8606c1618340e0bd767c5abebe7f1b2ee0","first_computed_at":"2026-07-28T02:24:05.205219Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-28T02:24:05.205219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ANXEp+tJkUbWiPM0ABJ5nmd66Z7pU+n8DE6IYPNIah3wOIEpaNtkInzLpFfJ2NPXST3yNMVDQAzmmAn1fkJyDA==","signature_status":"signed_v1","signed_at":"2026-07-28T02:24:05.206100Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.24465","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a0a7b15dc3b0f695fc7abb2b6aa5fd86bc2b5722a155cb109f8b91d89972b75","sha256:f7c2b0ba81f99d63913f1ed9ebf35a471d6bbc1302b3525b1c59bd0c5291c5d5"],"state_sha256":"71538f93e13720294da940016ebdf7b64f5f97f20e6b04fd50c10102912b7994"}