{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WRKYAYCF6XLMOPRONL4Z5YACPB","short_pith_number":"pith:WRKYAYCF","canonical_record":{"source":{"id":"2508.17780","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-08-25T08:23:41Z","cross_cats_sorted":[],"title_canon_sha256":"a7e7e65b135708e8fc983a32606574a0a6145fd6b77c34b3ebc825efd0db6333","abstract_canon_sha256":"255c111be349ee4eec1373a09734fc114ec52cc314866637d291e5ebfff7b813"},"schema_version":"1.0"},"canonical_sha256":"b455806045f5d6c73e2e6af99ee002787a18d543e90242af71056dcd34010fe2","source":{"kind":"arxiv","id":"2508.17780","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.17780","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"arxiv_version","alias_value":"2508.17780v1","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.17780","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_12","alias_value":"WRKYAYCF6XLM","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_16","alias_value":"WRKYAYCF6XLMOPRO","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_8","alias_value":"WRKYAYCF","created_at":"2026-07-05T11:58:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WRKYAYCF6XLMOPRONL4Z5YACPB","target":"record","payload":{"canonical_record":{"source":{"id":"2508.17780","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-08-25T08:23:41Z","cross_cats_sorted":[],"title_canon_sha256":"a7e7e65b135708e8fc983a32606574a0a6145fd6b77c34b3ebc825efd0db6333","abstract_canon_sha256":"255c111be349ee4eec1373a09734fc114ec52cc314866637d291e5ebfff7b813"},"schema_version":"1.0"},"canonical_sha256":"b455806045f5d6c73e2e6af99ee002787a18d543e90242af71056dcd34010fe2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:58:47.595653Z","signature_b64":"NyTBSwyYXMIf5Wzqfe+gkIlxdwAvwpgRPTFGMYRmfzAUv1kQOBfvzgyn0b65L3ottU2b2nthNdDASNwgMsRzBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b455806045f5d6c73e2e6af99ee002787a18d543e90242af71056dcd34010fe2","last_reissued_at":"2026-07-05T11:58:47.595091Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:58:47.595091Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.17780","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:58:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dOrF55BYk0hVdh7tz6+kRavs24cnXy03puLLoTVIYehdb2CACh+4nk45UGkGxV3j0MkG5nDwhzd2YJqABLcAAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:20:20.097431Z"},"content_sha256":"91f2cfd34ba189592a7e3007751531103c76e51aeb7ba560ce2fef9f236b5b25","schema_version":"1.0","event_id":"sha256:91f2cfd34ba189592a7e3007751531103c76e51aeb7ba560ce2fef9f236b5b25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WRKYAYCF6XLMOPRONL4Z5YACPB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Inference under Label Shift in Unsupervised Domain Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Jiwei Zhao, Seong-ho Lee, Yanyuan Ma","submitted_at":"2025-08-25T08:23:41Z","abstract_excerpt":"In many real-world applications, researchers aim to deploy models trained in a source domain to a target domain, where obtaining labeled data is often expensive, time-consuming, or even infeasible. While most existing literature assumes that the labeled source data and the unlabeled target data follow the same distribution, distribution shifts are common in practice. This paper focuses on label shift and develops efficient inference procedures for general parameters characterizing the unlabeled target population. A central idea is to model the outcome density ratio between the labeled and unla"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.17780","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/2508.17780/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:58:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"To7Z5p9e8CHpzh+P073Fex02EHnw+ZtvPZlw3jiozODhlFGuZXoTyUu9b+Y9dBB3wPWVplNBodsa78ZNd+BiAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T10:20:20.097990Z"},"content_sha256":"295316ea03e095685b8e35934c471b37f7d734930feba6671fed11e7f2fe2df6","schema_version":"1.0","event_id":"sha256:295316ea03e095685b8e35934c471b37f7d734930feba6671fed11e7f2fe2df6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/bundle.json","state_url":"https://pith.science/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-21T10:20:20Z","links":{"resolver":"https://pith.science/pith/WRKYAYCF6XLMOPRONL4Z5YACPB","bundle":"https://pith.science/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/bundle.json","state":"https://pith.science/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WRKYAYCF6XLMOPRONL4Z5YACPB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WRKYAYCF6XLMOPRONL4Z5YACPB","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":"255c111be349ee4eec1373a09734fc114ec52cc314866637d291e5ebfff7b813","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-08-25T08:23:41Z","title_canon_sha256":"a7e7e65b135708e8fc983a32606574a0a6145fd6b77c34b3ebc825efd0db6333"},"schema_version":"1.0","source":{"id":"2508.17780","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.17780","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"arxiv_version","alias_value":"2508.17780v1","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.17780","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_12","alias_value":"WRKYAYCF6XLM","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_16","alias_value":"WRKYAYCF6XLMOPRO","created_at":"2026-07-05T11:58:47Z"},{"alias_kind":"pith_short_8","alias_value":"WRKYAYCF","created_at":"2026-07-05T11:58:47Z"}],"graph_snapshots":[{"event_id":"sha256:295316ea03e095685b8e35934c471b37f7d734930feba6671fed11e7f2fe2df6","target":"graph","created_at":"2026-07-05T11:58:47Z","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/2508.17780/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many real-world applications, researchers aim to deploy models trained in a source domain to a target domain, where obtaining labeled data is often expensive, time-consuming, or even infeasible. While most existing literature assumes that the labeled source data and the unlabeled target data follow the same distribution, distribution shifts are common in practice. This paper focuses on label shift and develops efficient inference procedures for general parameters characterizing the unlabeled target population. A central idea is to model the outcome density ratio between the labeled and unla","authors_text":"Jiwei Zhao, Seong-ho Lee, Yanyuan Ma","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-08-25T08:23:41Z","title":"Efficient Inference under Label Shift in Unsupervised Domain Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.17780","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":"sha256:91f2cfd34ba189592a7e3007751531103c76e51aeb7ba560ce2fef9f236b5b25","target":"record","created_at":"2026-07-05T11:58:47Z","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":"255c111be349ee4eec1373a09734fc114ec52cc314866637d291e5ebfff7b813","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-08-25T08:23:41Z","title_canon_sha256":"a7e7e65b135708e8fc983a32606574a0a6145fd6b77c34b3ebc825efd0db6333"},"schema_version":"1.0","source":{"id":"2508.17780","kind":"arxiv","version":1}},"canonical_sha256":"b455806045f5d6c73e2e6af99ee002787a18d543e90242af71056dcd34010fe2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b455806045f5d6c73e2e6af99ee002787a18d543e90242af71056dcd34010fe2","first_computed_at":"2026-07-05T11:58:47.595091Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:58:47.595091Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NyTBSwyYXMIf5Wzqfe+gkIlxdwAvwpgRPTFGMYRmfzAUv1kQOBfvzgyn0b65L3ottU2b2nthNdDASNwgMsRzBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:58:47.595653Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.17780","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91f2cfd34ba189592a7e3007751531103c76e51aeb7ba560ce2fef9f236b5b25","sha256:295316ea03e095685b8e35934c471b37f7d734930feba6671fed11e7f2fe2df6"],"state_sha256":"06b01c2ec257e339b15e2c6e5c62d7acf7fe6c270cbdce818398ed21d73590d3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nDfaE7wTfVkSmDvnfooI0AgnlrLiU0Ymb+DOqfNvsbc6UwPNlrqWbj9HTLBwirrg3GtvDgfcUqIYatTY3QXEBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T10:20:20.100453Z","bundle_sha256":"83ab506b52746a46c10229d6470dd6600f63cee2a7b98d9d738a1ccda56f0229"}}