{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3FHKN7S4DTXGOPTVRSVSS43U65","short_pith_number":"pith:3FHKN7S4","schema_version":"1.0","canonical_sha256":"d94ea6fe5c1cee673e758cab297374f74c9d1b3c28e9ea420576af560f9ffb3e","source":{"kind":"arxiv","id":"2608.03607","version":1},"attestation_state":"computed","paper":{"title":"Beyond Predicting Responses: Conformal Inference for Latent Distributional Parameters","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Minxing Zheng, Shixiang Zhu, Wenbin Zhou","submitted_at":"2026-08-04T12:59:58Z","abstract_excerpt":"Many prediction problems seek to infer an unobserved, instance-specific parameter that governs the distribution of an observable response, even though the latent parameter is unavailable for both historical and future instances. We develop LatentCP, a prior-free conformal framework that constructs uncertainty sets for latent distributional parameters using only observed context--response pairs and a specified forward model. The method first constructs a conformal prediction set in the observable response space and then retains candidate latent parameters according to the probability their indu"},"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":"2608.03607","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-08-04T12:59:58Z","cross_cats_sorted":[],"title_canon_sha256":"0cd3b796759e6f6f02b5fafec90e49cbf0ce41bf9ac1b69bc17c504f002197e0","abstract_canon_sha256":"77501d56b97aec73cadf181180f395ba7336cc64b059437cd7fb58ae09356454"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-05T01:36:45.016421Z","signature_b64":"BwwI8QQYS5E22IgOmlQkyE8ANS0wmRlIQMqJzH1CJlYArUSPdBEYqsnnZQHSOf98rMcWCsZRvQui7nBkG+/JCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d94ea6fe5c1cee673e758cab297374f74c9d1b3c28e9ea420576af560f9ffb3e","last_reissued_at":"2026-08-05T01:36:45.014863Z","signature_status":"signed_v1","first_computed_at":"2026-08-05T01:36:45.014863Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Beyond Predicting Responses: Conformal Inference for Latent Distributional Parameters","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Minxing Zheng, Shixiang Zhu, Wenbin Zhou","submitted_at":"2026-08-04T12:59:58Z","abstract_excerpt":"Many prediction problems seek to infer an unobserved, instance-specific parameter that governs the distribution of an observable response, even though the latent parameter is unavailable for both historical and future instances. We develop LatentCP, a prior-free conformal framework that constructs uncertainty sets for latent distributional parameters using only observed context--response pairs and a specified forward model. The method first constructs a conformal prediction set in the observable response space and then retains candidate latent parameters according to the probability their indu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.03607","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/2608.03607/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":"2608.03607","created_at":"2026-08-05T01:36:45.015388+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.03607v1","created_at":"2026-08-05T01:36:45.015388+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.03607","created_at":"2026-08-05T01:36:45.015388+00:00"},{"alias_kind":"pith_short_12","alias_value":"3FHKN7S4DTXG","created_at":"2026-08-05T01:36:45.015388+00:00"},{"alias_kind":"pith_short_16","alias_value":"3FHKN7S4DTXGOPTV","created_at":"2026-08-05T01:36:45.015388+00:00"},{"alias_kind":"pith_short_8","alias_value":"3FHKN7S4","created_at":"2026-08-05T01:36:45.015388+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/3FHKN7S4DTXGOPTVRSVSS43U65","json":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65.json","graph_json":"https://pith.science/api/pith-number/3FHKN7S4DTXGOPTVRSVSS43U65/graph.json","events_json":"https://pith.science/api/pith-number/3FHKN7S4DTXGOPTVRSVSS43U65/events.json","paper":"https://pith.science/paper/3FHKN7S4"},"agent_actions":{"view_html":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65","download_json":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65.json","view_paper":"https://pith.science/paper/3FHKN7S4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.03607&json=true","fetch_graph":"https://pith.science/api/pith-number/3FHKN7S4DTXGOPTVRSVSS43U65/graph.json","fetch_events":"https://pith.science/api/pith-number/3FHKN7S4DTXGOPTVRSVSS43U65/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65/action/storage_attestation","attest_author":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65/action/author_attestation","sign_citation":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65/action/citation_signature","submit_replication":"https://pith.science/pith/3FHKN7S4DTXGOPTVRSVSS43U65/action/replication_record"}},"created_at":"2026-08-05T01:36:45.015388+00:00","updated_at":"2026-08-05T01:36:45.015388+00:00"}