{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:25I4VVRDLBHXUTPPKCARSFHWEZ","short_pith_number":"pith:25I4VVRD","schema_version":"1.0","canonical_sha256":"d751cad623584f7a4def50811914f626773e99754458449e3492f64da8bfc321","source":{"kind":"arxiv","id":"2607.18545","version":1},"attestation_state":"computed","paper":{"title":"Flexible Inference for Winners with Conditional Validity","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Lingjun Gao, Snigdha Panigrahi, Soham Bakshi, Zijun Gao","submitted_at":"2026-07-20T22:23:27Z","abstract_excerpt":"Researchers often select top-performing options or winners, based on a data-driven criterion, such as treatments, models, or model features and then report effect estimates for the selected winners. Naive post-selection estimates, however, are known to suffer from the winner's curse, producing systematically overoptimistic results. We introduce a flexible conditional inference method that corrects for this overoptimism through an adaptive exponential randomization scheme. Our method achieves selection quality that closely matches that of standard top-k selection, while also yielding shorter co"},"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":"2607.18545","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-20T22:23:27Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"1caa3730244dd5e437440e5be6774a0bb233b7b3d05547923776e8ae0f0e8ecf","abstract_canon_sha256":"d118c9473c55e30abb37cbc767fecc2e03010f259b58fc5d7d2aea917b593358"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-22T00:22:53.660977Z","signature_b64":"nwF+te/RI0ctq/jPVV+ZAlRpbnd90MI8zoapgmBXcJs5MASFIBBb7wJ+IEfCbt66n4Hg+rg9XgSgHXzdRp2KAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d751cad623584f7a4def50811914f626773e99754458449e3492f64da8bfc321","last_reissued_at":"2026-07-22T00:22:53.660168Z","signature_status":"signed_v1","first_computed_at":"2026-07-22T00:22:53.660168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Flexible Inference for Winners with Conditional Validity","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Lingjun Gao, Snigdha Panigrahi, Soham Bakshi, Zijun Gao","submitted_at":"2026-07-20T22:23:27Z","abstract_excerpt":"Researchers often select top-performing options or winners, based on a data-driven criterion, such as treatments, models, or model features and then report effect estimates for the selected winners. Naive post-selection estimates, however, are known to suffer from the winner's curse, producing systematically overoptimistic results. We introduce a flexible conditional inference method that corrects for this overoptimism through an adaptive exponential randomization scheme. Our method achieves selection quality that closely matches that of standard top-k selection, while also yielding shorter co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18545","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/2607.18545/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":"2607.18545","created_at":"2026-07-22T00:22:53.660590+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.18545v1","created_at":"2026-07-22T00:22:53.660590+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18545","created_at":"2026-07-22T00:22:53.660590+00:00"},{"alias_kind":"pith_short_12","alias_value":"25I4VVRDLBHX","created_at":"2026-07-22T00:22:53.660590+00:00"},{"alias_kind":"pith_short_16","alias_value":"25I4VVRDLBHXUTPP","created_at":"2026-07-22T00:22:53.660590+00:00"},{"alias_kind":"pith_short_8","alias_value":"25I4VVRD","created_at":"2026-07-22T00:22:53.660590+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/25I4VVRDLBHXUTPPKCARSFHWEZ","json":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ.json","graph_json":"https://pith.science/api/pith-number/25I4VVRDLBHXUTPPKCARSFHWEZ/graph.json","events_json":"https://pith.science/api/pith-number/25I4VVRDLBHXUTPPKCARSFHWEZ/events.json","paper":"https://pith.science/paper/25I4VVRD"},"agent_actions":{"view_html":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ","download_json":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ.json","view_paper":"https://pith.science/paper/25I4VVRD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.18545&json=true","fetch_graph":"https://pith.science/api/pith-number/25I4VVRDLBHXUTPPKCARSFHWEZ/graph.json","fetch_events":"https://pith.science/api/pith-number/25I4VVRDLBHXUTPPKCARSFHWEZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ/action/storage_attestation","attest_author":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ/action/author_attestation","sign_citation":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ/action/citation_signature","submit_replication":"https://pith.science/pith/25I4VVRDLBHXUTPPKCARSFHWEZ/action/replication_record"}},"created_at":"2026-07-22T00:22:53.660590+00:00","updated_at":"2026-07-22T00:22:53.660590+00:00"}