{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:52ER2NM3RCLIH3Q7URMF3MIIW6","short_pith_number":"pith:52ER2NM3","schema_version":"1.0","canonical_sha256":"ee891d359b889683ee1fa4585db108b7a2dba5dd35f5cb3d75ee0c863ddc4939","source":{"kind":"arxiv","id":"2607.19379","version":1},"attestation_state":"computed","paper":{"title":"Bayesian Wind Tunnels for Model Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Abhay Parekh, Siddhartha R Dalal, Vishal Misra","submitted_at":"2026-07-01T04:05:08Z","abstract_excerpt":"Prior work has shown that transformers can perform exact Bayesian filtering within a fixed\n  hypothesis class. Can they also perform Bayesian model selection -- identifying the correct\n  hypothesis class from data? We introduce model-selection Bayesian wind tunnels: controlled\n  environments where ground-truth posteriors over hypothesis classes are available in closed\n  form. Using fixed-point-free involutions -- whose defining property f(f(x))=x is purely\n  relational -- a 2.8M-parameter transformer achieves 0.01-bit entropy agreement with the\n  Bayesian optimum (3 seeds), with both integer t"},"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":"2607.19379","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-01T04:05:08Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"006e24f98cd80247802f55e33bf8eb59ff6b0c45525b6e4eac4c085afedbe800","abstract_canon_sha256":"76f4e3f78d8c0469103a347c3041952e5a55a0e7fd55dc3ad6a244ccc2b8d5d3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-23T00:23:47.101303Z","signature_b64":"RhOhPIg1wVmcL4olqPxAbRkUko7jsfyR/to40VrPjvIFejjTtAH4w40PDA3LLNYz58qIl5PtB2SOiMdm1GvfBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee891d359b889683ee1fa4585db108b7a2dba5dd35f5cb3d75ee0c863ddc4939","last_reissued_at":"2026-07-23T00:23:47.100446Z","signature_status":"signed_v1","first_computed_at":"2026-07-23T00:23:47.100446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian Wind Tunnels for Model Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Abhay Parekh, Siddhartha R Dalal, Vishal Misra","submitted_at":"2026-07-01T04:05:08Z","abstract_excerpt":"Prior work has shown that transformers can perform exact Bayesian filtering within a fixed\n  hypothesis class. Can they also perform Bayesian model selection -- identifying the correct\n  hypothesis class from data? We introduce model-selection Bayesian wind tunnels: controlled\n  environments where ground-truth posteriors over hypothesis classes are available in closed\n  form. Using fixed-point-free involutions -- whose defining property f(f(x))=x is purely\n  relational -- a 2.8M-parameter transformer achieves 0.01-bit entropy agreement with the\n  Bayesian optimum (3 seeds), with both integer t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.19379","kind":"arxiv","version":1},"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/2607.19379/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":"2607.19379","created_at":"2026-07-23T00:23:47.100854+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.19379v1","created_at":"2026-07-23T00:23:47.100854+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.19379","created_at":"2026-07-23T00:23:47.100854+00:00"},{"alias_kind":"pith_short_12","alias_value":"52ER2NM3RCLI","created_at":"2026-07-23T00:23:47.100854+00:00"},{"alias_kind":"pith_short_16","alias_value":"52ER2NM3RCLIH3Q7","created_at":"2026-07-23T00:23:47.100854+00:00"},{"alias_kind":"pith_short_8","alias_value":"52ER2NM3","created_at":"2026-07-23T00:23:47.100854+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6","json":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6.json","graph_json":"https://pith.science/api/pith-number/52ER2NM3RCLIH3Q7URMF3MIIW6/graph.json","events_json":"https://pith.science/api/pith-number/52ER2NM3RCLIH3Q7URMF3MIIW6/events.json","paper":"https://pith.science/paper/52ER2NM3"},"agent_actions":{"view_html":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6","download_json":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6.json","view_paper":"https://pith.science/paper/52ER2NM3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.19379&json=true","fetch_graph":"https://pith.science/api/pith-number/52ER2NM3RCLIH3Q7URMF3MIIW6/graph.json","fetch_events":"https://pith.science/api/pith-number/52ER2NM3RCLIH3Q7URMF3MIIW6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6/action/storage_attestation","attest_author":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6/action/author_attestation","sign_citation":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6/action/citation_signature","submit_replication":"https://pith.science/pith/52ER2NM3RCLIH3Q7URMF3MIIW6/action/replication_record"}},"created_at":"2026-07-23T00:23:47.100854+00:00","updated_at":"2026-07-23T00:23:47.100854+00:00"}