{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:XKXGZ3V6QHJBKC7GOB7JQDB2QV","short_pith_number":"pith:XKXGZ3V6","canonical_record":{"source":{"id":"2010.10596","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T20:08:42Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"473abd831672b8644923872fbe5ef2e2eb9ae683821e1a376129127621d00a46","abstract_canon_sha256":"e5209c2a6c119e9715b35f94a9b5ba43173b57a385f629bb074d1850479af4a6"},"schema_version":"1.0"},"canonical_sha256":"baae6ceebe81d2150be6707e980c3a8550ccaa490fa6c039b0395beb3f5568b2","source":{"kind":"arxiv","id":"2010.10596","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10596","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10596v3","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10596","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_12","alias_value":"XKXGZ3V6QHJB","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_16","alias_value":"XKXGZ3V6QHJBKC7G","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_8","alias_value":"XKXGZ3V6","created_at":"2026-07-05T05:16:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:XKXGZ3V6QHJBKC7GOB7JQDB2QV","target":"record","payload":{"canonical_record":{"source":{"id":"2010.10596","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T20:08:42Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"473abd831672b8644923872fbe5ef2e2eb9ae683821e1a376129127621d00a46","abstract_canon_sha256":"e5209c2a6c119e9715b35f94a9b5ba43173b57a385f629bb074d1850479af4a6"},"schema_version":"1.0"},"canonical_sha256":"baae6ceebe81d2150be6707e980c3a8550ccaa490fa6c039b0395beb3f5568b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:16:30.067369Z","signature_b64":"LVEjWwtfxr1f48wJpB2DwkitanshIGY2LVvIhKUnO1NoyiwaKeUbZzB2FbBcHhzSVteCDPQflNA2dXenWC0QCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"baae6ceebe81d2150be6707e980c3a8550ccaa490fa6c039b0395beb3f5568b2","last_reissued_at":"2026-07-05T05:16:30.066865Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:16:30.066865Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.10596","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":"2026-07-05T05:16:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"moPJ310QplLUcaAvYob7FgioN1/kImp3L2q9wADbhyM4y6dzZbgPEKP9iXWotuwjAXUmqYgs1mDxqLP9LOrkCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:59:33.923769Z"},"content_sha256":"8ff1647c567d2e864c9696eae602c887ed958527568f2c4637faf169da68ea22","schema_version":"1.0","event_id":"sha256:8ff1647c567d2e864c9696eae602c887ed958527568f2c4637faf169da68ea22"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:XKXGZ3V6QHJBKC7GOB7JQDB2QV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Chirag Shah, John P. Dickerson, Keegan E. Hines, Minh Hoang, Sahil Verma, Varich Boonsanong","submitted_at":"2020-10-20T20:08:42Z","abstract_excerpt":"Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders. Explaining, in a human-understandable way, the relationship between the input and output of machine learning models is essential to the development of trustworthy machine learning based systems. A burgeoning body of research seeks to define the goals and methods of explainability in machine learning. In this paper, we seek to review and categorize research on counterfactual explanations, a specific class of explanation that provides a link between"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10596","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/2010.10596/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":"2026-07-05T05:16:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/hR2z5+cLWpVbmvQbxyKxH8udI5/50haO7ar+XmpXmqDrxUwx+YmcOg4enjIgBGP75MiXgv/PXUAbBMm36EACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:59:33.924395Z"},"content_sha256":"d4c093d1ed045e1bafeb85306e9a6808ed0c5eb46091d5c46b224efd1efaa0a8","schema_version":"1.0","event_id":"sha256:d4c093d1ed045e1bafeb85306e9a6808ed0c5eb46091d5c46b224efd1efaa0a8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/bundle.json","state_url":"https://pith.science/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/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":"2026-07-05T15:59:33Z","links":{"resolver":"https://pith.science/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV","bundle":"https://pith.science/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/bundle.json","state":"https://pith.science/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XKXGZ3V6QHJBKC7GOB7JQDB2QV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XKXGZ3V6QHJBKC7GOB7JQDB2QV","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":"e5209c2a6c119e9715b35f94a9b5ba43173b57a385f629bb074d1850479af4a6","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T20:08:42Z","title_canon_sha256":"473abd831672b8644923872fbe5ef2e2eb9ae683821e1a376129127621d00a46"},"schema_version":"1.0","source":{"id":"2010.10596","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10596","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10596v3","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10596","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_12","alias_value":"XKXGZ3V6QHJB","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_16","alias_value":"XKXGZ3V6QHJBKC7G","created_at":"2026-07-05T05:16:30Z"},{"alias_kind":"pith_short_8","alias_value":"XKXGZ3V6","created_at":"2026-07-05T05:16:30Z"}],"graph_snapshots":[{"event_id":"sha256:d4c093d1ed045e1bafeb85306e9a6808ed0c5eb46091d5c46b224efd1efaa0a8","target":"graph","created_at":"2026-07-05T05:16:30Z","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/2010.10596/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders. Explaining, in a human-understandable way, the relationship between the input and output of machine learning models is essential to the development of trustworthy machine learning based systems. A burgeoning body of research seeks to define the goals and methods of explainability in machine learning. In this paper, we seek to review and categorize research on counterfactual explanations, a specific class of explanation that provides a link between","authors_text":"Chirag Shah, John P. Dickerson, Keegan E. Hines, Minh Hoang, Sahil Verma, Varich Boonsanong","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T20:08:42Z","title":"Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10596","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":"sha256:8ff1647c567d2e864c9696eae602c887ed958527568f2c4637faf169da68ea22","target":"record","created_at":"2026-07-05T05:16:30Z","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":"e5209c2a6c119e9715b35f94a9b5ba43173b57a385f629bb074d1850479af4a6","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T20:08:42Z","title_canon_sha256":"473abd831672b8644923872fbe5ef2e2eb9ae683821e1a376129127621d00a46"},"schema_version":"1.0","source":{"id":"2010.10596","kind":"arxiv","version":3}},"canonical_sha256":"baae6ceebe81d2150be6707e980c3a8550ccaa490fa6c039b0395beb3f5568b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"baae6ceebe81d2150be6707e980c3a8550ccaa490fa6c039b0395beb3f5568b2","first_computed_at":"2026-07-05T05:16:30.066865Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:16:30.066865Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LVEjWwtfxr1f48wJpB2DwkitanshIGY2LVvIhKUnO1NoyiwaKeUbZzB2FbBcHhzSVteCDPQflNA2dXenWC0QCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:16:30.067369Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.10596","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8ff1647c567d2e864c9696eae602c887ed958527568f2c4637faf169da68ea22","sha256:d4c093d1ed045e1bafeb85306e9a6808ed0c5eb46091d5c46b224efd1efaa0a8"],"state_sha256":"a2133cf2419d2b0fb2db562ea424521b80b39d73ee7d26b9946b6b9284b2e0a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QiJ1KV5CCb1g3mjUbukfEsVI7VKuIXbYbXyApFXeSQP2pMtFxesY5maOgPs9TycZFcbIo1oWupB4lLd5K+LQCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:59:33.927276Z","bundle_sha256":"de1616b87c2c0728678f5b8fffc7a269a70251a962807ac47057e6283b6898eb"}}