{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ZNLX5SIDYLRPSPGJXEGKMXPY3D","short_pith_number":"pith:ZNLX5SID","canonical_record":{"source":{"id":"2004.00221","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T04:04:03Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"d229613ad120fa07aff5f7018d05c7b55ce335c5cf04a70738e8d750b9b0c30e","abstract_canon_sha256":"56515ec5c327018ec6f1cddfae03e8619dd2898e5df82e8859856e53e74b548b"},"schema_version":"1.0"},"canonical_sha256":"cb577ec903c2e2f93cc9b90ca65df8d8ce0423126590a9a9bf2dcfb769f7a8ff","source":{"kind":"arxiv","id":"2004.00221","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00221","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00221v3","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00221","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_12","alias_value":"ZNLX5SIDYLRP","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_16","alias_value":"ZNLX5SIDYLRPSPGJ","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_8","alias_value":"ZNLX5SID","created_at":"2026-07-05T02:10:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ZNLX5SIDYLRPSPGJXEGKMXPY3D","target":"record","payload":{"canonical_record":{"source":{"id":"2004.00221","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T04:04:03Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"d229613ad120fa07aff5f7018d05c7b55ce335c5cf04a70738e8d750b9b0c30e","abstract_canon_sha256":"56515ec5c327018ec6f1cddfae03e8619dd2898e5df82e8859856e53e74b548b"},"schema_version":"1.0"},"canonical_sha256":"cb577ec903c2e2f93cc9b90ca65df8d8ce0423126590a9a9bf2dcfb769f7a8ff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:10:24.532604Z","signature_b64":"cy5GhzhH+24OVYGYZ9AQUstY/pJRn3EuHw8hW4hpDE/KFqYUpSw2dQajPYl+13oF9783wHPI7rkpkiMNCQ5VAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb577ec903c2e2f93cc9b90ca65df8d8ce0423126590a9a9bf2dcfb769f7a8ff","last_reissued_at":"2026-07-05T02:10:24.532098Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:10:24.532098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.00221","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:10:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pKDQfzxOmWBS8Uk1aZBzsrUE3lih9soGWEByxrPgqO9wrki/1RCbH2FOUX4E0C5McLamFWwnOY+tuH9nKpYVAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:13:49.491911Z"},"content_sha256":"1f4016c720803065f03710089c726b31bd4b7929a2271a79a957560911665480","schema_version":"1.0","event_id":"sha256:1f4016c720803065f03710089c726b31bd4b7929a2271a79a957560911665480"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ZNLX5SIDYLRPSPGJXEGKMXPY3D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NBDT: Neural-Backed Decision Trees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"cs.CV","authors_text":"Alvin Wan, Daniel Ho, Henry Jin, Jihan Yin, Joseph E. Gonzalez, Lisa Dunlap, Sarah Adel Bargal, Scott Lee, Suzanne Petryk","submitted_at":"2020-04-01T04:04:03Z","abstract_excerpt":"Machine learning applications such as finance and medicine demand accurate and justifiable predictions, barring most deep learning methods from use. In response, previous work combines decision trees with deep learning, yielding models that (1) sacrifice interpretability for accuracy or (2) sacrifice accuracy for interpretability. We forgo this dilemma by jointly improving accuracy and interpretability using Neural-Backed Decision Trees (NBDTs). NBDTs replace a neural network's final linear layer with a differentiable sequence of decisions and a surrogate loss. This forces the model to learn h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00221","kind":"arxiv","version":3},"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/2004.00221/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":"2026-07-05T02:10:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"swqQVWbex35ASuIOwHGtAZRtAfCiUGMWMkF0F2EQoYvnLesUJlFT+rdichIAyIVizLaow+FnKinEqt1R2As9DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:13:49.492279Z"},"content_sha256":"8098676a5c171114f98d7f662b44c6ef608a457d16bce66bec78d9263f34b5e2","schema_version":"1.0","event_id":"sha256:8098676a5c171114f98d7f662b44c6ef608a457d16bce66bec78d9263f34b5e2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/bundle.json","state_url":"https://pith.science/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/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":"2026-07-07T14:13:49Z","links":{"resolver":"https://pith.science/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D","bundle":"https://pith.science/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/bundle.json","state":"https://pith.science/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZNLX5SIDYLRPSPGJXEGKMXPY3D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ZNLX5SIDYLRPSPGJXEGKMXPY3D","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":"56515ec5c327018ec6f1cddfae03e8619dd2898e5df82e8859856e53e74b548b","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T04:04:03Z","title_canon_sha256":"d229613ad120fa07aff5f7018d05c7b55ce335c5cf04a70738e8d750b9b0c30e"},"schema_version":"1.0","source":{"id":"2004.00221","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.00221","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"arxiv_version","alias_value":"2004.00221v3","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.00221","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_12","alias_value":"ZNLX5SIDYLRP","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_16","alias_value":"ZNLX5SIDYLRPSPGJ","created_at":"2026-07-05T02:10:24Z"},{"alias_kind":"pith_short_8","alias_value":"ZNLX5SID","created_at":"2026-07-05T02:10:24Z"}],"graph_snapshots":[{"event_id":"sha256:8098676a5c171114f98d7f662b44c6ef608a457d16bce66bec78d9263f34b5e2","target":"graph","created_at":"2026-07-05T02:10:24Z","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/2004.00221/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning applications such as finance and medicine demand accurate and justifiable predictions, barring most deep learning methods from use. In response, previous work combines decision trees with deep learning, yielding models that (1) sacrifice interpretability for accuracy or (2) sacrifice accuracy for interpretability. We forgo this dilemma by jointly improving accuracy and interpretability using Neural-Backed Decision Trees (NBDTs). NBDTs replace a neural network's final linear layer with a differentiable sequence of decisions and a surrogate loss. This forces the model to learn h","authors_text":"Alvin Wan, Daniel Ho, Henry Jin, Jihan Yin, Joseph E. Gonzalez, Lisa Dunlap, Sarah Adel Bargal, Scott Lee, Suzanne Petryk","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T04:04:03Z","title":"NBDT: Neural-Backed Decision Trees"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.00221","kind":"arxiv","version":3},"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":"sha256:1f4016c720803065f03710089c726b31bd4b7929a2271a79a957560911665480","target":"record","created_at":"2026-07-05T02:10:24Z","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":"56515ec5c327018ec6f1cddfae03e8619dd2898e5df82e8859856e53e74b548b","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-01T04:04:03Z","title_canon_sha256":"d229613ad120fa07aff5f7018d05c7b55ce335c5cf04a70738e8d750b9b0c30e"},"schema_version":"1.0","source":{"id":"2004.00221","kind":"arxiv","version":3}},"canonical_sha256":"cb577ec903c2e2f93cc9b90ca65df8d8ce0423126590a9a9bf2dcfb769f7a8ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb577ec903c2e2f93cc9b90ca65df8d8ce0423126590a9a9bf2dcfb769f7a8ff","first_computed_at":"2026-07-05T02:10:24.532098Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:10:24.532098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cy5GhzhH+24OVYGYZ9AQUstY/pJRn3EuHw8hW4hpDE/KFqYUpSw2dQajPYl+13oF9783wHPI7rkpkiMNCQ5VAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:10:24.532604Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.00221","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f4016c720803065f03710089c726b31bd4b7929a2271a79a957560911665480","sha256:8098676a5c171114f98d7f662b44c6ef608a457d16bce66bec78d9263f34b5e2"],"state_sha256":"88f4c6c8b8850e14e3c2bc7d2f5df61396e36ee1999e4d7057359bff5876e878"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EBU771vzrp6mjKalkTm1nqzN911XpGFGQGPLahwFg4T665mLNqq7s03q5oEBNaSYsQ/iG6jmGPtCqcRKTUggCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T14:13:49.494373Z","bundle_sha256":"95a65ae6b849895e7079cae4ed404d06b6a2429d06a2727fbf52ba6259620019"}}