{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:FHFC4IHC2SGU7KR64SCVEWPSPZ","short_pith_number":"pith:FHFC4IHC","canonical_record":{"source":{"id":"2208.08579","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-08-18T00:48:04Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"9b83962e138fd68df22ef2c7fab283e4bc0ab97f96dbb10e0384850319b95d80","abstract_canon_sha256":"06e95f1a8daed7b26e301fed0705e7136cd3e550712b52dfda4c70037ec32d04"},"schema_version":"1.0"},"canonical_sha256":"29ca2e20e2d48d4faa3ee4855259f27e484dc6f0681f59d30994f93b2f11bef6","source":{"kind":"arxiv","id":"2208.08579","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.08579","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"arxiv_version","alias_value":"2208.08579v2","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.08579","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_12","alias_value":"FHFC4IHC2SGU","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_16","alias_value":"FHFC4IHC2SGU7KR6","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_8","alias_value":"FHFC4IHC","created_at":"2026-07-05T05:59:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:FHFC4IHC2SGU7KR64SCVEWPSPZ","target":"record","payload":{"canonical_record":{"source":{"id":"2208.08579","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-08-18T00:48:04Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"9b83962e138fd68df22ef2c7fab283e4bc0ab97f96dbb10e0384850319b95d80","abstract_canon_sha256":"06e95f1a8daed7b26e301fed0705e7136cd3e550712b52dfda4c70037ec32d04"},"schema_version":"1.0"},"canonical_sha256":"29ca2e20e2d48d4faa3ee4855259f27e484dc6f0681f59d30994f93b2f11bef6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:38.846642Z","signature_b64":"KPhGz7fzwJVyQLzHtHET7pKUUOpurDiEnyDveVXZCrvGgnqBhUzk31JEY3pO79GC20GMTmCrjRwKBSBmTj3xAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"29ca2e20e2d48d4faa3ee4855259f27e484dc6f0681f59d30994f93b2f11bef6","last_reissued_at":"2026-07-05T05:59:38.846175Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:38.846175Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.08579","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":"2026-07-05T05:59:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b2WrexsXQdXSv1eAp913p48/pdx7oTK6AVNZGlH3Ve23ltnsNOzUnvCWKoCdVhpfa6y7YADTB/8LjFCEJ7ZwAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T15:56:43.501390Z"},"content_sha256":"8372b50aaec6ca9d68f5314135a56577428d6f880debdb37edcac19c3a85320b","schema_version":"1.0","event_id":"sha256:8372b50aaec6ca9d68f5314135a56577428d6f880debdb37edcac19c3a85320b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:FHFC4IHC2SGU7KR64SCVEWPSPZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DIET: Conditional independence testing with marginal dependence measures of residual information","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"stat.ME","authors_text":"Aahlad Manas Puli, Mukund Sudarshan, Rajesh Ranganath, Wesley Tansey","submitted_at":"2022-08-18T00:48:04Z","abstract_excerpt":"Conditional randomization tests (CRTs) assess whether a variable $x$ is predictive of another variable $y$, having observed covariates $z$. CRTs require fitting a large number of predictive models, which is often computationally intractable. Existing solutions to reduce the cost of CRTs typically split the dataset into a train and test portion, or rely on heuristics for interactions, both of which lead to a loss in power. We propose the decoupled independence test (DIET), an algorithm that avoids both of these issues by leveraging marginal independence statistics to test conditional independen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.08579","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/2208.08579/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":"2026-07-05T05:59:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"siOGMNt/51MXBcF42DGz0e0ZJXd8yVDKIOLLk+UGKsaIwLfaFd/DSR+g6tsqbQZJE87E+QF1KcWufcUKS3tuCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T15:56:43.501772Z"},"content_sha256":"0ad58242f7a09e938d6467136de27e9c422a1e2f9da674bd14993bb6e6c2c406","schema_version":"1.0","event_id":"sha256:0ad58242f7a09e938d6467136de27e9c422a1e2f9da674bd14993bb6e6c2c406"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/bundle.json","state_url":"https://pith.science/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/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":"2026-07-08T15:56:43Z","links":{"resolver":"https://pith.science/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ","bundle":"https://pith.science/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/bundle.json","state":"https://pith.science/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FHFC4IHC2SGU7KR64SCVEWPSPZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:FHFC4IHC2SGU7KR64SCVEWPSPZ","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":"06e95f1a8daed7b26e301fed0705e7136cd3e550712b52dfda4c70037ec32d04","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-08-18T00:48:04Z","title_canon_sha256":"9b83962e138fd68df22ef2c7fab283e4bc0ab97f96dbb10e0384850319b95d80"},"schema_version":"1.0","source":{"id":"2208.08579","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.08579","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"arxiv_version","alias_value":"2208.08579v2","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.08579","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_12","alias_value":"FHFC4IHC2SGU","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_16","alias_value":"FHFC4IHC2SGU7KR6","created_at":"2026-07-05T05:59:38Z"},{"alias_kind":"pith_short_8","alias_value":"FHFC4IHC","created_at":"2026-07-05T05:59:38Z"}],"graph_snapshots":[{"event_id":"sha256:0ad58242f7a09e938d6467136de27e9c422a1e2f9da674bd14993bb6e6c2c406","target":"graph","created_at":"2026-07-05T05:59:38Z","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/2208.08579/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conditional randomization tests (CRTs) assess whether a variable $x$ is predictive of another variable $y$, having observed covariates $z$. CRTs require fitting a large number of predictive models, which is often computationally intractable. Existing solutions to reduce the cost of CRTs typically split the dataset into a train and test portion, or rely on heuristics for interactions, both of which lead to a loss in power. We propose the decoupled independence test (DIET), an algorithm that avoids both of these issues by leveraging marginal independence statistics to test conditional independen","authors_text":"Aahlad Manas Puli, Mukund Sudarshan, Rajesh Ranganath, Wesley Tansey","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-08-18T00:48:04Z","title":"DIET: Conditional independence testing with marginal dependence measures of residual information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.08579","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":"sha256:8372b50aaec6ca9d68f5314135a56577428d6f880debdb37edcac19c3a85320b","target":"record","created_at":"2026-07-05T05:59:38Z","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":"06e95f1a8daed7b26e301fed0705e7136cd3e550712b52dfda4c70037ec32d04","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-08-18T00:48:04Z","title_canon_sha256":"9b83962e138fd68df22ef2c7fab283e4bc0ab97f96dbb10e0384850319b95d80"},"schema_version":"1.0","source":{"id":"2208.08579","kind":"arxiv","version":2}},"canonical_sha256":"29ca2e20e2d48d4faa3ee4855259f27e484dc6f0681f59d30994f93b2f11bef6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29ca2e20e2d48d4faa3ee4855259f27e484dc6f0681f59d30994f93b2f11bef6","first_computed_at":"2026-07-05T05:59:38.846175Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:38.846175Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KPhGz7fzwJVyQLzHtHET7pKUUOpurDiEnyDveVXZCrvGgnqBhUzk31JEY3pO79GC20GMTmCrjRwKBSBmTj3xAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:38.846642Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.08579","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8372b50aaec6ca9d68f5314135a56577428d6f880debdb37edcac19c3a85320b","sha256:0ad58242f7a09e938d6467136de27e9c422a1e2f9da674bd14993bb6e6c2c406"],"state_sha256":"a5036a4deff591bf4b2ed2d33c171bbb93483aa45be4ec46edcee1218268884c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7LD0VtSAaao97qF+K4eQAFS/wLpsFv0MYkQHeIUIK1h2uDBbQpgnexa6g3tewsN3pb6RH2j0u6uDz6PhZss8Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T15:56:43.504024Z","bundle_sha256":"51857c4ddbf777bf91e5b7e2351f2d3b8d030a1484999599bbeecf31d74e1e47"}}