{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:P4JOE7JIXNATPTHTSXGO67MWPL","short_pith_number":"pith:P4JOE7JI","canonical_record":{"source":{"id":"2408.02045","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-08-04T14:45:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e12babc842dad767947660b6e8e370121f21f4b32fb497c439542b8b61d1152e","abstract_canon_sha256":"42c73f11a5db8569642bd2f77988ee44e31532e0e2f156ff70f26d1556196e9f"},"schema_version":"1.0"},"canonical_sha256":"7f12e27d28bb4137ccf395ccef7d967aee1af6417e710e06f5523c84d1a8ecd1","source":{"kind":"arxiv","id":"2408.02045","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02045","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02045v1","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02045","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_12","alias_value":"P4JOE7JIXNAT","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_16","alias_value":"P4JOE7JIXNATPTHT","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_8","alias_value":"P4JOE7JI","created_at":"2026-07-05T08:52:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:P4JOE7JIXNATPTHTSXGO67MWPL","target":"record","payload":{"canonical_record":{"source":{"id":"2408.02045","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-08-04T14:45:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e12babc842dad767947660b6e8e370121f21f4b32fb497c439542b8b61d1152e","abstract_canon_sha256":"42c73f11a5db8569642bd2f77988ee44e31532e0e2f156ff70f26d1556196e9f"},"schema_version":"1.0"},"canonical_sha256":"7f12e27d28bb4137ccf395ccef7d967aee1af6417e710e06f5523c84d1a8ecd1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:52:06.691958Z","signature_b64":"CjLHw2vRxZe3lwkfXhyGZeuRVPS6AbvP/nFQM/8Y+lsM55eD4AiQA5gwDdBwUlF/wafDvhJsg/BCsGlVmWYuBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f12e27d28bb4137ccf395ccef7d967aee1af6417e710e06f5523c84d1a8ecd1","last_reissued_at":"2026-07-05T08:52:06.691490Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:52:06.691490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.02045","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":"2026-07-05T08:52:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NAMQ17YXZBZulxEz2eABukFYdU7Z72XQIxXZSPgsPEJMJA3W2w1858m+Xk93/zpsGF+IMTdkUTbItqTKvff/DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:23:11.224007Z"},"content_sha256":"40350ce6faa80b177f4cbc3106b52391015f263e3081d132c7efd1812eb15ab6","schema_version":"1.0","event_id":"sha256:40350ce6faa80b177f4cbc3106b52391015f263e3081d132c7efd1812eb15ab6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:P4JOE7JIXNATPTHTSXGO67MWPL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Lei Zhang, Lin Liu, Qinshuo Liu, Xi-An Li, Xinyao Ji, Zhonghua Liu, Zixin Wang","submitted_at":"2024-08-04T14:45:26Z","abstract_excerpt":"Semiparametric statistics play a pivotal role in a wide range of domains, including but not limited to missing data, causal inference, and transfer learning, to name a few. In many settings, semiparametric theory leads to (nearly) statistically optimal procedures that yet involve numerically solving Fredholm integral equations of the second kind. Traditional numerical methods, such as polynomial or spline approximations, are difficult to scale to multi-dimensional problems. Alternatively, statisticians may choose to approximate the original integral equations by ones with closed-form solutions"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02045","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/2408.02045/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":"2026-07-05T08:52:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qd0+BxhnZocviZpLIj/UoW9tHzkIUMnI6FeWFM3WqKC1fjVurjUBMpiKwxF0V5st6fOPmelyMaQ2+BBmsaWKDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:23:11.224397Z"},"content_sha256":"8911927f4d4cbee46ff9b3f76eab0d029f8a15230af915b67fcf427c7a444231","schema_version":"1.0","event_id":"sha256:8911927f4d4cbee46ff9b3f76eab0d029f8a15230af915b67fcf427c7a444231"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P4JOE7JIXNATPTHTSXGO67MWPL/bundle.json","state_url":"https://pith.science/pith/P4JOE7JIXNATPTHTSXGO67MWPL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P4JOE7JIXNATPTHTSXGO67MWPL/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":"2026-07-08T19:23:11Z","links":{"resolver":"https://pith.science/pith/P4JOE7JIXNATPTHTSXGO67MWPL","bundle":"https://pith.science/pith/P4JOE7JIXNATPTHTSXGO67MWPL/bundle.json","state":"https://pith.science/pith/P4JOE7JIXNATPTHTSXGO67MWPL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P4JOE7JIXNATPTHTSXGO67MWPL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:P4JOE7JIXNATPTHTSXGO67MWPL","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":"42c73f11a5db8569642bd2f77988ee44e31532e0e2f156ff70f26d1556196e9f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-08-04T14:45:26Z","title_canon_sha256":"e12babc842dad767947660b6e8e370121f21f4b32fb497c439542b8b61d1152e"},"schema_version":"1.0","source":{"id":"2408.02045","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02045","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02045v1","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02045","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_12","alias_value":"P4JOE7JIXNAT","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_16","alias_value":"P4JOE7JIXNATPTHT","created_at":"2026-07-05T08:52:06Z"},{"alias_kind":"pith_short_8","alias_value":"P4JOE7JI","created_at":"2026-07-05T08:52:06Z"}],"graph_snapshots":[{"event_id":"sha256:8911927f4d4cbee46ff9b3f76eab0d029f8a15230af915b67fcf427c7a444231","target":"graph","created_at":"2026-07-05T08:52:06Z","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/2408.02045/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semiparametric statistics play a pivotal role in a wide range of domains, including but not limited to missing data, causal inference, and transfer learning, to name a few. In many settings, semiparametric theory leads to (nearly) statistically optimal procedures that yet involve numerically solving Fredholm integral equations of the second kind. Traditional numerical methods, such as polynomial or spline approximations, are difficult to scale to multi-dimensional problems. Alternatively, statisticians may choose to approximate the original integral equations by ones with closed-form solutions","authors_text":"Lei Zhang, Lin Liu, Qinshuo Liu, Xi-An Li, Xinyao Ji, Zhonghua Liu, Zixin Wang","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-08-04T14:45:26Z","title":"DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02045","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":"sha256:40350ce6faa80b177f4cbc3106b52391015f263e3081d132c7efd1812eb15ab6","target":"record","created_at":"2026-07-05T08:52:06Z","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":"42c73f11a5db8569642bd2f77988ee44e31532e0e2f156ff70f26d1556196e9f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-08-04T14:45:26Z","title_canon_sha256":"e12babc842dad767947660b6e8e370121f21f4b32fb497c439542b8b61d1152e"},"schema_version":"1.0","source":{"id":"2408.02045","kind":"arxiv","version":1}},"canonical_sha256":"7f12e27d28bb4137ccf395ccef7d967aee1af6417e710e06f5523c84d1a8ecd1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f12e27d28bb4137ccf395ccef7d967aee1af6417e710e06f5523c84d1a8ecd1","first_computed_at":"2026-07-05T08:52:06.691490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:52:06.691490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CjLHw2vRxZe3lwkfXhyGZeuRVPS6AbvP/nFQM/8Y+lsM55eD4AiQA5gwDdBwUlF/wafDvhJsg/BCsGlVmWYuBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:52:06.691958Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.02045","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:40350ce6faa80b177f4cbc3106b52391015f263e3081d132c7efd1812eb15ab6","sha256:8911927f4d4cbee46ff9b3f76eab0d029f8a15230af915b67fcf427c7a444231"],"state_sha256":"d4c4c0156216ad2008d37a5092d8e243725a9cdf6a2d4f1bdcf196b3149d014b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nUo9tQl19oXhIe4TZTAG214flscNG4w6QAlUQdNTcT9UBTxsKA2Aw+FQAjG1p3bzoKqT4yzZB1MNXN8jIEQ0Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T19:23:11.226428Z","bundle_sha256":"25aa1cb5f79e9783c58a4dd4cc4ce141e7dab9691b92b0352614cd9854870b22"}}