{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:N6GGVXZB27HOV4HBO6YZQIIP2Z","short_pith_number":"pith:N6GGVXZB","canonical_record":{"source":{"id":"2502.10095","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-14T11:36:04Z","cross_cats_sorted":[],"title_canon_sha256":"fa1e6af062bf4ea6571a3dcf71a9f317441fbfe41ab999bd030762b75045b10b","abstract_canon_sha256":"47ca266c7e9c0e972ecc58fa698cef1f42fe53757cf914fb692bcbfd9e68b139"},"schema_version":"1.0"},"canonical_sha256":"6f8c6adf21d7ceeaf0e177b198210fd66e54a8482da033d5d440911abe990fb8","source":{"kind":"arxiv","id":"2502.10095","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.10095","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"arxiv_version","alias_value":"2502.10095v2","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.10095","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_12","alias_value":"N6GGVXZB27HO","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_16","alias_value":"N6GGVXZB27HOV4HB","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_8","alias_value":"N6GGVXZB","created_at":"2026-07-05T11:05:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:N6GGVXZB27HOV4HBO6YZQIIP2Z","target":"record","payload":{"canonical_record":{"source":{"id":"2502.10095","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-14T11:36:04Z","cross_cats_sorted":[],"title_canon_sha256":"fa1e6af062bf4ea6571a3dcf71a9f317441fbfe41ab999bd030762b75045b10b","abstract_canon_sha256":"47ca266c7e9c0e972ecc58fa698cef1f42fe53757cf914fb692bcbfd9e68b139"},"schema_version":"1.0"},"canonical_sha256":"6f8c6adf21d7ceeaf0e177b198210fd66e54a8482da033d5d440911abe990fb8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:05:40.095775Z","signature_b64":"QB92XTWKR6qF8EyN0GSQQqQMMpaYMF/RewmjZ70m5IKmmrjoBi/ACRUDXTX0CuHBkP/254XchDErv3E1s0L1Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f8c6adf21d7ceeaf0e177b198210fd66e54a8482da033d5d440911abe990fb8","last_reissued_at":"2026-07-05T11:05:40.095262Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:05:40.095262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.10095","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:05:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"++Nsir/UVxLR9Bzayn63wKni8FuGE+Ik6Ow51GSOL79NBBPC0mWgRixs5NrEuvuYN89o4zS7A8MP/l0hy0piBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T19:04:20.119563Z"},"content_sha256":"8b0c093de30d2fa937fc11334779d7aa7af77f8f5b2daab0c4390cd7f0a3d648","schema_version":"1.0","event_id":"sha256:8b0c093de30d2fa937fc11334779d7aa7af77f8f5b2daab0c4390cd7f0a3d648"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:N6GGVXZB27HOV4HBO6YZQIIP2Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Representation Learning on Out of Distribution in Tabular Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Achmad Ginanjar, Priyanka Singh, Wen Hua, Xue Li","submitted_at":"2025-02-14T11:36:04Z","abstract_excerpt":"The open-world assumption in model development suggests that a model might lack sufficient information to adequately handle data that is entirely distinct or out of distribution (OOD). While deep learning methods have shown promising results in handling OOD data through generalization techniques, they often require specialized hardware that may not be accessible to all users. We present TCL, a lightweight yet effective solution that operates efficiently on standard CPU hardware. Our approach adapts contrastive learning principles specifically for tabular data structures, incorporating full mat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.10095","kind":"arxiv","version":2},"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/2502.10095/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":"2026-07-05T11:05:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V6Vy2eSEhU2/GoECzbrxo8Mqm1Q7JxyBCS99zFErHl4mxAkYrXVP7x3glcu3d78dKTb53tsYc4qwJUWttLM/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T19:04:20.119936Z"},"content_sha256":"a13bf02c9e8eb601533334b6d4ecc9f0fbbc571ac957ca26cb89efa1b89fd4c6","schema_version":"1.0","event_id":"sha256:a13bf02c9e8eb601533334b6d4ecc9f0fbbc571ac957ca26cb89efa1b89fd4c6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/bundle.json","state_url":"https://pith.science/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/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":"2026-07-13T19:04:20Z","links":{"resolver":"https://pith.science/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z","bundle":"https://pith.science/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/bundle.json","state":"https://pith.science/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N6GGVXZB27HOV4HBO6YZQIIP2Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:N6GGVXZB27HOV4HBO6YZQIIP2Z","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":"47ca266c7e9c0e972ecc58fa698cef1f42fe53757cf914fb692bcbfd9e68b139","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-14T11:36:04Z","title_canon_sha256":"fa1e6af062bf4ea6571a3dcf71a9f317441fbfe41ab999bd030762b75045b10b"},"schema_version":"1.0","source":{"id":"2502.10095","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.10095","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"arxiv_version","alias_value":"2502.10095v2","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.10095","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_12","alias_value":"N6GGVXZB27HO","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_16","alias_value":"N6GGVXZB27HOV4HB","created_at":"2026-07-05T11:05:40Z"},{"alias_kind":"pith_short_8","alias_value":"N6GGVXZB","created_at":"2026-07-05T11:05:40Z"}],"graph_snapshots":[{"event_id":"sha256:a13bf02c9e8eb601533334b6d4ecc9f0fbbc571ac957ca26cb89efa1b89fd4c6","target":"graph","created_at":"2026-07-05T11:05:40Z","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/2502.10095/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The open-world assumption in model development suggests that a model might lack sufficient information to adequately handle data that is entirely distinct or out of distribution (OOD). While deep learning methods have shown promising results in handling OOD data through generalization techniques, they often require specialized hardware that may not be accessible to all users. We present TCL, a lightweight yet effective solution that operates efficiently on standard CPU hardware. Our approach adapts contrastive learning principles specifically for tabular data structures, incorporating full mat","authors_text":"Achmad Ginanjar, Priyanka Singh, Wen Hua, Xue Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-14T11:36:04Z","title":"Representation Learning on Out of Distribution in Tabular Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.10095","kind":"arxiv","version":2},"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":"sha256:8b0c093de30d2fa937fc11334779d7aa7af77f8f5b2daab0c4390cd7f0a3d648","target":"record","created_at":"2026-07-05T11:05:40Z","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":"47ca266c7e9c0e972ecc58fa698cef1f42fe53757cf914fb692bcbfd9e68b139","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-14T11:36:04Z","title_canon_sha256":"fa1e6af062bf4ea6571a3dcf71a9f317441fbfe41ab999bd030762b75045b10b"},"schema_version":"1.0","source":{"id":"2502.10095","kind":"arxiv","version":2}},"canonical_sha256":"6f8c6adf21d7ceeaf0e177b198210fd66e54a8482da033d5d440911abe990fb8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6f8c6adf21d7ceeaf0e177b198210fd66e54a8482da033d5d440911abe990fb8","first_computed_at":"2026-07-05T11:05:40.095262Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:05:40.095262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QB92XTWKR6qF8EyN0GSQQqQMMpaYMF/RewmjZ70m5IKmmrjoBi/ACRUDXTX0CuHBkP/254XchDErv3E1s0L1Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:05:40.095775Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.10095","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8b0c093de30d2fa937fc11334779d7aa7af77f8f5b2daab0c4390cd7f0a3d648","sha256:a13bf02c9e8eb601533334b6d4ecc9f0fbbc571ac957ca26cb89efa1b89fd4c6"],"state_sha256":"640d45cdd440ce79c20dd8ca411faecb0c5579165a7ab6b0759dd71094853433"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pAEEiNruKcnEjIY9Y3j9cQfwyHSlJwwpxaI/Ej2I/z/mLJrxwx1Ji03/FF9OIdKd2mbJHqbbOsNtH5QanY4lAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T19:04:20.123247Z","bundle_sha256":"754c4a4fdbb18b5421761e235706463702e4b6b58f9a6c17c3812d4de8ed23df"}}