{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:SUKLQPJSF7IAL4FV5USPZPFVEW","short_pith_number":"pith:SUKLQPJS","canonical_record":{"source":{"id":"2106.07754","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-14T20:48:48Z","cross_cats_sorted":["cs.CY","cs.LG","stat.ML"],"title_canon_sha256":"efcb7a809b2b081c500a29373729407728587590230a826d327f173bd2787d77","abstract_canon_sha256":"f7c73ff7e695590b98bec0c8fe14f0f2f7671ab053a8eff7bc135dcce4bfdc3b"},"schema_version":"1.0"},"canonical_sha256":"9514b83d322fd005f0b5ed24fcbcb525b6831a5bc89e5325a75e40bbd5a3ae2e","source":{"kind":"arxiv","id":"2106.07754","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.07754","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"arxiv_version","alias_value":"2106.07754v2","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.07754","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_12","alias_value":"SUKLQPJSF7IA","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"SUKLQPJSF7IAL4FV","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"SUKLQPJS","created_at":"2026-07-05T03:29:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:SUKLQPJSF7IAL4FV5USPZPFVEW","target":"record","payload":{"canonical_record":{"source":{"id":"2106.07754","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-14T20:48:48Z","cross_cats_sorted":["cs.CY","cs.LG","stat.ML"],"title_canon_sha256":"efcb7a809b2b081c500a29373729407728587590230a826d327f173bd2787d77","abstract_canon_sha256":"f7c73ff7e695590b98bec0c8fe14f0f2f7671ab053a8eff7bc135dcce4bfdc3b"},"schema_version":"1.0"},"canonical_sha256":"9514b83d322fd005f0b5ed24fcbcb525b6831a5bc89e5325a75e40bbd5a3ae2e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:29:50.085267Z","signature_b64":"S7c/vyZOnBcn4fk+SQ5AP539qnfjwpqp6GQt0d/Q8O2fM8TJLaiWselBMiQa6FYymUyMkKiCPAa2yn7WjoV5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9514b83d322fd005f0b5ed24fcbcb525b6831a5bc89e5325a75e40bbd5a3ae2e","last_reissued_at":"2026-07-05T03:29:50.084835Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:29:50.084835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.07754","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":"2026-07-05T03:29:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fbCCTtUehY8ZUffcSDvH+haWdB0yXFSnFXJjXDZjGPhJWJfpVjrhoF8TN0j1ajyDwHiHYEiWSJhLU8GSyNjvDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:48:11.992894Z"},"content_sha256":"d93042ac154915ee4b9448a32371c6ba73794cae8486ea7c3b523c0e39e36d2b","schema_version":"1.0","event_id":"sha256:d93042ac154915ee4b9448a32371c6ba73794cae8486ea7c3b523c0e39e36d2b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:SUKLQPJSF7IAL4FV5USPZPFVEW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Counterfactual Explanations as Interventions in Latent Space","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CY","cs.LG","stat.ML"],"primary_cat":"cs.AI","authors_text":"Alessandro Castelnovo, Beatriz San Miguel Gonzalez, Daniele Regoli, Riccardo Crupi","submitted_at":"2021-06-14T20:48:48Z","abstract_excerpt":"Explainable Artificial Intelligence (XAI) is a set of techniques that allows the understanding of both technical and non-technical aspects of Artificial Intelligence (AI) systems. XAI is crucial to help satisfying the increasingly important demand of \\emph{trustworthy} Artificial Intelligence, characterized by fundamental characteristics such as respect of human autonomy, prevention of harm, transparency, accountability, etc. Within XAI techniques, counterfactual explanations aim to provide to end users a set of features (and their corresponding values) that need to be changed in order to achi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.07754","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/2106.07754/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":"2026-07-05T03:29:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v9xF7s3dfRueWgdeYRFKXV447JHXn15RW4ycQ1VVPSyJjUlwC7LZEPIuQPzTzmwo7ZwjyBylwaxyc8uyUPfhCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:48:11.993265Z"},"content_sha256":"cd7fafde56f207ae1fae03f8de88862e1c3cd44602993221363f319e5ce315c2","schema_version":"1.0","event_id":"sha256:cd7fafde56f207ae1fae03f8de88862e1c3cd44602993221363f319e5ce315c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/bundle.json","state_url":"https://pith.science/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/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":"2026-07-06T15:48:11Z","links":{"resolver":"https://pith.science/pith/SUKLQPJSF7IAL4FV5USPZPFVEW","bundle":"https://pith.science/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/bundle.json","state":"https://pith.science/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SUKLQPJSF7IAL4FV5USPZPFVEW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:SUKLQPJSF7IAL4FV5USPZPFVEW","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":"f7c73ff7e695590b98bec0c8fe14f0f2f7671ab053a8eff7bc135dcce4bfdc3b","cross_cats_sorted":["cs.CY","cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-14T20:48:48Z","title_canon_sha256":"efcb7a809b2b081c500a29373729407728587590230a826d327f173bd2787d77"},"schema_version":"1.0","source":{"id":"2106.07754","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.07754","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"arxiv_version","alias_value":"2106.07754v2","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.07754","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_12","alias_value":"SUKLQPJSF7IA","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"SUKLQPJSF7IAL4FV","created_at":"2026-07-05T03:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"SUKLQPJS","created_at":"2026-07-05T03:29:50Z"}],"graph_snapshots":[{"event_id":"sha256:cd7fafde56f207ae1fae03f8de88862e1c3cd44602993221363f319e5ce315c2","target":"graph","created_at":"2026-07-05T03:29:50Z","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/2106.07754/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Explainable Artificial Intelligence (XAI) is a set of techniques that allows the understanding of both technical and non-technical aspects of Artificial Intelligence (AI) systems. XAI is crucial to help satisfying the increasingly important demand of \\emph{trustworthy} Artificial Intelligence, characterized by fundamental characteristics such as respect of human autonomy, prevention of harm, transparency, accountability, etc. Within XAI techniques, counterfactual explanations aim to provide to end users a set of features (and their corresponding values) that need to be changed in order to achi","authors_text":"Alessandro Castelnovo, Beatriz San Miguel Gonzalez, Daniele Regoli, Riccardo Crupi","cross_cats":["cs.CY","cs.LG","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-14T20:48:48Z","title":"Counterfactual Explanations as Interventions in Latent Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.07754","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:d93042ac154915ee4b9448a32371c6ba73794cae8486ea7c3b523c0e39e36d2b","target":"record","created_at":"2026-07-05T03:29:50Z","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":"f7c73ff7e695590b98bec0c8fe14f0f2f7671ab053a8eff7bc135dcce4bfdc3b","cross_cats_sorted":["cs.CY","cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-14T20:48:48Z","title_canon_sha256":"efcb7a809b2b081c500a29373729407728587590230a826d327f173bd2787d77"},"schema_version":"1.0","source":{"id":"2106.07754","kind":"arxiv","version":2}},"canonical_sha256":"9514b83d322fd005f0b5ed24fcbcb525b6831a5bc89e5325a75e40bbd5a3ae2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9514b83d322fd005f0b5ed24fcbcb525b6831a5bc89e5325a75e40bbd5a3ae2e","first_computed_at":"2026-07-05T03:29:50.084835Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:29:50.084835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S7c/vyZOnBcn4fk+SQ5AP539qnfjwpqp6GQt0d/Q8O2fM8TJLaiWselBMiQa6FYymUyMkKiCPAa2yn7WjoV5DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:29:50.085267Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.07754","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d93042ac154915ee4b9448a32371c6ba73794cae8486ea7c3b523c0e39e36d2b","sha256:cd7fafde56f207ae1fae03f8de88862e1c3cd44602993221363f319e5ce315c2"],"state_sha256":"1776704a37d4536b3489866132449436786ada518770468c7bcf6930dc3327a7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yFPklSmh+ADMi/ZahvigUhUWuuV1EYKoctBlIKbPcIreKQrRQHXMnxh2YgGyBNV5CjBcEjJR3etLwm9rIQQpDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T15:48:11.995267Z","bundle_sha256":"012aaaa4a7b9c98cd268e4289214222ea9c6e1c4ba5d14ac3c75e5beef79401e"}}