{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:EVUIT3DLETS3KBJPS6UNCVWKLR","short_pith_number":"pith:EVUIT3DL","schema_version":"1.0","canonical_sha256":"256889ec6b24e5b5052f97a8d156ca5c636e7fe1612aa8bef148cdcff408a25b","source":{"kind":"arxiv","id":"2406.01627","version":2},"attestation_state":"computed","paper":{"title":"GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"q-bio.GN","authors_text":"Cheng Tan, Jiahui Li, Siyuan Li, Stan Z. Li, Yajing Bai, Yufei Huang, Zelin Zang, Zicheng Liu","submitted_at":"2024-06-01T08:01:05Z","abstract_excerpt":"The Genomic Foundation Model (GFM) paradigm is expected to facilitate the extraction of generalizable representations from massive genomic data, thereby enabling their application across a spectrum of downstream applications. Despite advancements, a lack of evaluation framework makes it difficult to ensure equitable assessment due to experimental settings, model intricacy, benchmark datasets, and reproducibility challenges. In the absence of standardization, comparative analyses risk becoming biased and unreliable. To surmount this impasse, we introduce GenBench, a comprehensive benchmarking s"},"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":"2406.01627","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.GN","submitted_at":"2024-06-01T08:01:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"171b16f488106611f59b9fa4c12d026d6cfcf573ced5d878552126788f3bc6d4","abstract_canon_sha256":"77f55c967c1fba74fcfc211926aecfbc0c1ad6c0166d9f1c5843ddb542b877b0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:49.940909Z","signature_b64":"d3fZJ/J90jLAjXEWQTYL7mZnUuiqOkM7aWfFubnAp9Zc4YZOq3ZQ13bk+sZDbAJ0MGlKAW4VC8OJEakqkHPZAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"256889ec6b24e5b5052f97a8d156ca5c636e7fe1612aa8bef148cdcff408a25b","last_reissued_at":"2026-07-05T08:27:49.940375Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:49.940375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"q-bio.GN","authors_text":"Cheng Tan, Jiahui Li, Siyuan Li, Stan Z. Li, Yajing Bai, Yufei Huang, Zelin Zang, Zicheng Liu","submitted_at":"2024-06-01T08:01:05Z","abstract_excerpt":"The Genomic Foundation Model (GFM) paradigm is expected to facilitate the extraction of generalizable representations from massive genomic data, thereby enabling their application across a spectrum of downstream applications. Despite advancements, a lack of evaluation framework makes it difficult to ensure equitable assessment due to experimental settings, model intricacy, benchmark datasets, and reproducibility challenges. In the absence of standardization, comparative analyses risk becoming biased and unreliable. To surmount this impasse, we introduce GenBench, a comprehensive benchmarking s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.01627","kind":"arxiv","version":2},"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/2406.01627/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":"2406.01627","created_at":"2026-07-05T08:27:49.940434+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.01627v2","created_at":"2026-07-05T08:27:49.940434+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.01627","created_at":"2026-07-05T08:27:49.940434+00:00"},{"alias_kind":"pith_short_12","alias_value":"EVUIT3DLETS3","created_at":"2026-07-05T08:27:49.940434+00:00"},{"alias_kind":"pith_short_16","alias_value":"EVUIT3DLETS3KBJP","created_at":"2026-07-05T08:27:49.940434+00:00"},{"alias_kind":"pith_short_8","alias_value":"EVUIT3DL","created_at":"2026-07-05T08:27:49.940434+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.25388","citing_title":"ViroBench: Benchmarking Nucleotide Foundation Models on Viral Genomics Tasks","ref_index":25,"is_internal_anchor":false},{"citing_arxiv_id":"2605.08685","citing_title":"Event Fields: Learning Latent Event Structure for Waveform Foundation Models","ref_index":30,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR","json":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR.json","graph_json":"https://pith.science/api/pith-number/EVUIT3DLETS3KBJPS6UNCVWKLR/graph.json","events_json":"https://pith.science/api/pith-number/EVUIT3DLETS3KBJPS6UNCVWKLR/events.json","paper":"https://pith.science/paper/EVUIT3DL"},"agent_actions":{"view_html":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR","download_json":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR.json","view_paper":"https://pith.science/paper/EVUIT3DL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.01627&json=true","fetch_graph":"https://pith.science/api/pith-number/EVUIT3DLETS3KBJPS6UNCVWKLR/graph.json","fetch_events":"https://pith.science/api/pith-number/EVUIT3DLETS3KBJPS6UNCVWKLR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR/action/storage_attestation","attest_author":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR/action/author_attestation","sign_citation":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR/action/citation_signature","submit_replication":"https://pith.science/pith/EVUIT3DLETS3KBJPS6UNCVWKLR/action/replication_record"}},"created_at":"2026-07-05T08:27:49.940434+00:00","updated_at":"2026-07-05T08:27:49.940434+00:00"}