{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5BNUYIP7RKEFEUIIZE4CIASIVC","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":"e516448c19eeb0d38180fdf045438ab00a02ed47518644b846349c1a1eb16e3a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-11T17:54:44Z","title_canon_sha256":"c0362798fad5378682b8f439c1f1fd82eff213c73a042f39974026db2da7e98c"},"schema_version":"1.0","source":{"id":"2308.06262","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.06262","created_at":"2026-07-05T06:40:25Z"},{"alias_kind":"arxiv_version","alias_value":"2308.06262v1","created_at":"2026-07-05T06:40:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.06262","created_at":"2026-07-05T06:40:25Z"},{"alias_kind":"pith_short_12","alias_value":"5BNUYIP7RKEF","created_at":"2026-07-05T06:40:25Z"},{"alias_kind":"pith_short_16","alias_value":"5BNUYIP7RKEFEUII","created_at":"2026-07-05T06:40:25Z"},{"alias_kind":"pith_short_8","alias_value":"5BNUYIP7","created_at":"2026-07-05T06:40:25Z"}],"graph_snapshots":[{"event_id":"sha256:fa707aeffa24e7a00fb7281c5007f719d7e8cb03a2d1852ae7bfb0e73ab8f236","target":"graph","created_at":"2026-07-05T06:40:25Z","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/2308.06262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper investigates an under-explored but important problem: given a collection of pre-trained neural networks, predicting their performance on each multi-modal task without fine-tuning them, such as image recognition, referring, captioning, visual question answering, and text question answering. A brute-force approach is to finetune all models on all target datasets, bringing high computational costs. Although recent-advanced approaches employed lightweight metrics to measure models' transferability,they often depend heavily on the prior knowledge of a single task, making them inapplicabl","authors_text":"Chonghe Jiang, Fanqing Meng, Kaipeng Zhang, Ping Luo, Wenqi Shao, Yu Qiao, Zhanglin Peng","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-11T17:54:44Z","title":"Foundation Model is Efficient Multimodal Multitask Model Selector"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.06262","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":"sha256:62689f09245692c7b6820a5032384927b40087921441bade344a9e4645ecbb49","target":"record","created_at":"2026-07-05T06:40:25Z","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":"e516448c19eeb0d38180fdf045438ab00a02ed47518644b846349c1a1eb16e3a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-11T17:54:44Z","title_canon_sha256":"c0362798fad5378682b8f439c1f1fd82eff213c73a042f39974026db2da7e98c"},"schema_version":"1.0","source":{"id":"2308.06262","kind":"arxiv","version":1}},"canonical_sha256":"e85b4c21ff8a88525108c938240248a89f2d3706a5b04a4a6afe6d520524ab13","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e85b4c21ff8a88525108c938240248a89f2d3706a5b04a4a6afe6d520524ab13","first_computed_at":"2026-07-05T06:40:25.543931Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:40:25.543931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jXW6g3U48IjUneckt12yPyPAWdKSK5eSY/Jqm+qKs10VClR3pts9S+PURmZOhJPYHCM5OK5EQXKAoBZFqMX8AA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:40:25.544373Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.06262","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:62689f09245692c7b6820a5032384927b40087921441bade344a9e4645ecbb49","sha256:fa707aeffa24e7a00fb7281c5007f719d7e8cb03a2d1852ae7bfb0e73ab8f236"],"state_sha256":"9c6f62e8ce5f2c0480c419a573979879ec67cf8954fcf081a5ccaa671693530e"}