{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:YPVCES33RDWJVCLQEJCPJPPOQF","short_pith_number":"pith:YPVCES33","schema_version":"1.0","canonical_sha256":"c3ea224b7b88ec9a89702244f4bdee8171e7e65e628d0f1bc9680bece2ac598a","source":{"kind":"arxiv","id":"2406.16608","version":1},"attestation_state":"computed","paper":{"title":"When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Chuan-Xian Ren, You-Wei Luo","submitted_at":"2024-06-24T12:47:21Z","abstract_excerpt":"As a crucial step toward real-world learning scenarios with changing environments, dataset shift theory and invariant representation learning algorithm have been extensively studied to relax the identical distribution assumption in classical learning setting. Among the different assumptions on the essential of shifting distributions, generalized label shift (GLS) is the latest developed one which shows great potential to deal with the complex factors within the shift. In this paper, we aim to explore the limitations of current dataset shift theory and algorithm, and further provide new insight"},"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":"2406.16608","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-24T12:47:21Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"f89fbcab3beba08edfe4a49dea224d31c847dd211c08e5209314905c3f8daee1","abstract_canon_sha256":"e5b9071b2fd4980947bfc18a4b19b92294fa04c6068133caf2eea1b0fe0fddb8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:36:01.275213Z","signature_b64":"/5KSIUQwSY/+ImW8NUblUGfAT/otagazGcg3mLB6Mutwtf4HGoitlvj6RmuqHnSgb3aVyWnUTTNxYfH7EZCOAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3ea224b7b88ec9a89702244f4bdee8171e7e65e628d0f1bc9680bece2ac598a","last_reissued_at":"2026-07-05T08:36:01.274770Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:36:01.274770Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Chuan-Xian Ren, You-Wei Luo","submitted_at":"2024-06-24T12:47:21Z","abstract_excerpt":"As a crucial step toward real-world learning scenarios with changing environments, dataset shift theory and invariant representation learning algorithm have been extensively studied to relax the identical distribution assumption in classical learning setting. Among the different assumptions on the essential of shifting distributions, generalized label shift (GLS) is the latest developed one which shows great potential to deal with the complex factors within the shift. In this paper, we aim to explore the limitations of current dataset shift theory and algorithm, and further provide new insight"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.16608","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/2406.16608/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":"2406.16608","created_at":"2026-07-05T08:36:01.274827+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.16608v1","created_at":"2026-07-05T08:36:01.274827+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.16608","created_at":"2026-07-05T08:36:01.274827+00:00"},{"alias_kind":"pith_short_12","alias_value":"YPVCES33RDWJ","created_at":"2026-07-05T08:36:01.274827+00:00"},{"alias_kind":"pith_short_16","alias_value":"YPVCES33RDWJVCLQ","created_at":"2026-07-05T08:36:01.274827+00:00"},{"alias_kind":"pith_short_8","alias_value":"YPVCES33","created_at":"2026-07-05T08:36:01.274827+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/YPVCES33RDWJVCLQEJCPJPPOQF","json":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF.json","graph_json":"https://pith.science/api/pith-number/YPVCES33RDWJVCLQEJCPJPPOQF/graph.json","events_json":"https://pith.science/api/pith-number/YPVCES33RDWJVCLQEJCPJPPOQF/events.json","paper":"https://pith.science/paper/YPVCES33"},"agent_actions":{"view_html":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF","download_json":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF.json","view_paper":"https://pith.science/paper/YPVCES33","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.16608&json=true","fetch_graph":"https://pith.science/api/pith-number/YPVCES33RDWJVCLQEJCPJPPOQF/graph.json","fetch_events":"https://pith.science/api/pith-number/YPVCES33RDWJVCLQEJCPJPPOQF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF/action/storage_attestation","attest_author":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF/action/author_attestation","sign_citation":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF/action/citation_signature","submit_replication":"https://pith.science/pith/YPVCES33RDWJVCLQEJCPJPPOQF/action/replication_record"}},"created_at":"2026-07-05T08:36:01.274827+00:00","updated_at":"2026-07-05T08:36:01.274827+00:00"}