{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UMBH4L2VQJACWWS6QGVMR4RETJ","short_pith_number":"pith:UMBH4L2V","canonical_record":{"source":{"id":"2403.03772","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T15:06:11Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"b98ae9bd2fd7fa395e6259bb44957286e44004fbb796444127d2e43a04748428","abstract_canon_sha256":"442e91bd05d9c33e8628c3e88fce3389c7f4ed550c5df7292c28db238652e095"},"schema_version":"1.0"},"canonical_sha256":"a3027e2f5582402b5a5e81aac8f2249a4443065458ce0853ecc00aae98cb3844","source":{"kind":"arxiv","id":"2403.03772","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.03772","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"arxiv_version","alias_value":"2403.03772v1","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03772","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_12","alias_value":"UMBH4L2VQJAC","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_16","alias_value":"UMBH4L2VQJACWWS6","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_8","alias_value":"UMBH4L2V","created_at":"2026-07-05T07:53:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UMBH4L2VQJACWWS6QGVMR4RETJ","target":"record","payload":{"canonical_record":{"source":{"id":"2403.03772","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T15:06:11Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"b98ae9bd2fd7fa395e6259bb44957286e44004fbb796444127d2e43a04748428","abstract_canon_sha256":"442e91bd05d9c33e8628c3e88fce3389c7f4ed550c5df7292c28db238652e095"},"schema_version":"1.0"},"canonical_sha256":"a3027e2f5582402b5a5e81aac8f2249a4443065458ce0853ecc00aae98cb3844","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:01.356551Z","signature_b64":"G3BJqJTCh7vRJMYmsgdozHJ7vy2OhCRc3zjISd/mRIldiG6DgK8xfBnORyrXE7T011X5/bPV18PMtoGN5rgDDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3027e2f5582402b5a5e81aac8f2249a4443065458ce0853ecc00aae98cb3844","last_reissued_at":"2026-07-05T07:53:01.356185Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:01.356185Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.03772","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":"2026-07-05T07:53:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eB1MnTjQ/gEpdlWGIYTXc3vOTNhrJmtHdGyqKHj7NO9F8nKheKDpzFb+Nmy7UQ/dCXNaStiWJQCZrCgpNC3cBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:33:57.715322Z"},"content_sha256":"e10262f2f825e16539d69c6ce09f46f16892ff8995d9c9fc35ed5225f7a2af33","schema_version":"1.0","event_id":"sha256:e10262f2f825e16539d69c6ce09f46f16892ff8995d9c9fc35ed5225f7a2af33"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UMBH4L2VQJACWWS6QGVMR4RETJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"J. Zico Kolter, Victor Akinwande","submitted_at":"2024-03-06T15:06:11Z","abstract_excerpt":"Existing causal discovery methods based on combinatorial optimization or search are slow, prohibiting their application on large-scale datasets. In response, more recent methods attempt to address this limitation by formulating causal discovery as structure learning with continuous optimization but such approaches thus far provide no statistical guarantees. In this paper, we show that by efficiently parallelizing existing causal discovery methods, we can in fact scale them to thousands of dimensions, making them practical for substantially larger-scale problems. In particular, we parallelize t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03772","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/2403.03772/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":"2026-07-05T07:53:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W0fpI5AvMk5CMFGWT9fOIViifB6c9JFJWe2AnBYJnbDMXwUyxuq4EiiCC5rzEnbyMUMdQXNX8+504vYj4q9ZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:33:57.715816Z"},"content_sha256":"20cb48fd8c5054fd0375057df38d1241a02267ef4c9d4f984d32b968d3d2d2f1","schema_version":"1.0","event_id":"sha256:20cb48fd8c5054fd0375057df38d1241a02267ef4c9d4f984d32b968d3d2d2f1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/bundle.json","state_url":"https://pith.science/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/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":"2026-08-11T19:33:57Z","links":{"resolver":"https://pith.science/pith/UMBH4L2VQJACWWS6QGVMR4RETJ","bundle":"https://pith.science/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/bundle.json","state":"https://pith.science/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UMBH4L2VQJACWWS6QGVMR4RETJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UMBH4L2VQJACWWS6QGVMR4RETJ","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":"442e91bd05d9c33e8628c3e88fce3389c7f4ed550c5df7292c28db238652e095","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T15:06:11Z","title_canon_sha256":"b98ae9bd2fd7fa395e6259bb44957286e44004fbb796444127d2e43a04748428"},"schema_version":"1.0","source":{"id":"2403.03772","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.03772","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"arxiv_version","alias_value":"2403.03772v1","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03772","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_12","alias_value":"UMBH4L2VQJAC","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_16","alias_value":"UMBH4L2VQJACWWS6","created_at":"2026-07-05T07:53:01Z"},{"alias_kind":"pith_short_8","alias_value":"UMBH4L2V","created_at":"2026-07-05T07:53:01Z"}],"graph_snapshots":[{"event_id":"sha256:20cb48fd8c5054fd0375057df38d1241a02267ef4c9d4f984d32b968d3d2d2f1","target":"graph","created_at":"2026-07-05T07:53:01Z","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/2403.03772/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing causal discovery methods based on combinatorial optimization or search are slow, prohibiting their application on large-scale datasets. In response, more recent methods attempt to address this limitation by formulating causal discovery as structure learning with continuous optimization but such approaches thus far provide no statistical guarantees. In this paper, we show that by efficiently parallelizing existing causal discovery methods, we can in fact scale them to thousands of dimensions, making them practical for substantially larger-scale problems. In particular, we parallelize t","authors_text":"J. Zico Kolter, Victor Akinwande","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T15:06:11Z","title":"AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03772","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:e10262f2f825e16539d69c6ce09f46f16892ff8995d9c9fc35ed5225f7a2af33","target":"record","created_at":"2026-07-05T07:53:01Z","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":"442e91bd05d9c33e8628c3e88fce3389c7f4ed550c5df7292c28db238652e095","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T15:06:11Z","title_canon_sha256":"b98ae9bd2fd7fa395e6259bb44957286e44004fbb796444127d2e43a04748428"},"schema_version":"1.0","source":{"id":"2403.03772","kind":"arxiv","version":1}},"canonical_sha256":"a3027e2f5582402b5a5e81aac8f2249a4443065458ce0853ecc00aae98cb3844","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a3027e2f5582402b5a5e81aac8f2249a4443065458ce0853ecc00aae98cb3844","first_computed_at":"2026-07-05T07:53:01.356185Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:01.356185Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G3BJqJTCh7vRJMYmsgdozHJ7vy2OhCRc3zjISd/mRIldiG6DgK8xfBnORyrXE7T011X5/bPV18PMtoGN5rgDDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:01.356551Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.03772","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e10262f2f825e16539d69c6ce09f46f16892ff8995d9c9fc35ed5225f7a2af33","sha256:20cb48fd8c5054fd0375057df38d1241a02267ef4c9d4f984d32b968d3d2d2f1"],"state_sha256":"9f014a0f5b3666f4d60b55813955c469ae1efb6e293f929d1da593016e8b200f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T5cHyFz94qFjillZ4jVKxazmsxUeksYTWve4JnwO1YudXPQrOxTV9DWy9/GgZzeZM5/NRwukTTgcyzZ/pCFbAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T19:33:57.719495Z","bundle_sha256":"1bf657d15ef8ddb6809f3998b577fa62c6cfc47cd12d67da3d4840fa148a3ae2"}}