{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:HNBBDPPV5URNNWLQ4QOVKGBM6H","short_pith_number":"pith:HNBBDPPV","canonical_record":{"source":{"id":"2607.01306","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-01T16:55:06Z","cross_cats_sorted":[],"title_canon_sha256":"4225f3c025cfd21906b47eec4ed9d450d4850ac74fe3d432cbabea03fd8c88fb","abstract_canon_sha256":"d472ffbbfa596924e743d67870b7e7f9fc1dc44178d2d3ad3f63967ad643fa46"},"schema_version":"1.0"},"canonical_sha256":"3b4211bdf5ed22d6d970e41d55182cf1c0afa5e32d89cdf79cf61bba3a2f4c36","source":{"kind":"arxiv","id":"2607.01306","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.01306","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"arxiv_version","alias_value":"2607.01306v1","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.01306","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_12","alias_value":"HNBBDPPV5URN","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_16","alias_value":"HNBBDPPV5URNNWLQ","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_8","alias_value":"HNBBDPPV","created_at":"2026-07-03T00:16:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:HNBBDPPV5URNNWLQ4QOVKGBM6H","target":"record","payload":{"canonical_record":{"source":{"id":"2607.01306","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-01T16:55:06Z","cross_cats_sorted":[],"title_canon_sha256":"4225f3c025cfd21906b47eec4ed9d450d4850ac74fe3d432cbabea03fd8c88fb","abstract_canon_sha256":"d472ffbbfa596924e743d67870b7e7f9fc1dc44178d2d3ad3f63967ad643fa46"},"schema_version":"1.0"},"canonical_sha256":"3b4211bdf5ed22d6d970e41d55182cf1c0afa5e32d89cdf79cf61bba3a2f4c36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T00:16:56.916013Z","signature_b64":"d0cby7elux/GQB7IbCn0rUIlEVMmR7amLFT2PXOT5aeJw4v2W+dtQoKk+9kUhNmbLmkdPVi62XDymmhP7je8AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b4211bdf5ed22d6d970e41d55182cf1c0afa5e32d89cdf79cf61bba3a2f4c36","last_reissued_at":"2026-07-03T00:16:56.915605Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T00:16:56.915605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.01306","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":"2026-07-03T00:16:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jEbv3oy6y7prpN8iy7l8xN1X/ldYtt7irUO3cO9DeTGk68fpPqb1i1L+HxmdOVbXwGEx9NzdPgeHdcOj/n1FDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T20:02:38.907940Z"},"content_sha256":"a63e604e3186b9bf0f5e61d7e8df8d1229c1d78073cbbb423baf3582e5b3539c","schema_version":"1.0","event_id":"sha256:a63e604e3186b9bf0f5e61d7e8df8d1229c1d78073cbbb423baf3582e5b3539c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:HNBBDPPV5URNNWLQ4QOVKGBM6H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Fadi Al Machot, Liyanapathiranage Sudeepika Wajirakumari Samarathunga, Martin Thomas Horsch, Pavel Iakovets","submitted_at":"2026-07-01T16:55:06Z","abstract_excerpt":"Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many existing methods successfully generate prediction-changing alternatives, they often produce unrealistic or infeasible recommendations due to a lack of explicit mechanisms for incorporating domain knowledge and intervention constraints. Neuro-symbolic AI offers a promising direction by combining data-driven predictive models with symbolic reasoning capable of representing human-understandable rules and feasible actions. This paper presents PACE"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.01306","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/2607.01306/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":"2026-07-03T00:16:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vtSjz/2PhW0iqpAhwGwMeX8ndYWSGlnEKc8JeOGkaPAmHMlZYyk/jfTalEZ2go8p3FLta/pWWr1ntjynYMVuAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T20:02:38.908321Z"},"content_sha256":"fe868de261a75068b3fbe0ea90cad9b5fce83c886d866f6c39f82d020c71c18b","schema_version":"1.0","event_id":"sha256:fe868de261a75068b3fbe0ea90cad9b5fce83c886d866f6c39f82d020c71c18b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/bundle.json","state_url":"https://pith.science/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/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":"2026-08-22T20:02:38Z","links":{"resolver":"https://pith.science/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H","bundle":"https://pith.science/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/bundle.json","state":"https://pith.science/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HNBBDPPV5URNNWLQ4QOVKGBM6H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HNBBDPPV5URNNWLQ4QOVKGBM6H","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":"d472ffbbfa596924e743d67870b7e7f9fc1dc44178d2d3ad3f63967ad643fa46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-01T16:55:06Z","title_canon_sha256":"4225f3c025cfd21906b47eec4ed9d450d4850ac74fe3d432cbabea03fd8c88fb"},"schema_version":"1.0","source":{"id":"2607.01306","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.01306","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"arxiv_version","alias_value":"2607.01306v1","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.01306","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_12","alias_value":"HNBBDPPV5URN","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_16","alias_value":"HNBBDPPV5URNNWLQ","created_at":"2026-07-03T00:16:56Z"},{"alias_kind":"pith_short_8","alias_value":"HNBBDPPV","created_at":"2026-07-03T00:16:56Z"}],"graph_snapshots":[{"event_id":"sha256:fe868de261a75068b3fbe0ea90cad9b5fce83c886d866f6c39f82d020c71c18b","target":"graph","created_at":"2026-07-03T00:16:56Z","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/2607.01306/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many existing methods successfully generate prediction-changing alternatives, they often produce unrealistic or infeasible recommendations due to a lack of explicit mechanisms for incorporating domain knowledge and intervention constraints. Neuro-symbolic AI offers a promising direction by combining data-driven predictive models with symbolic reasoning capable of representing human-understandable rules and feasible actions. This paper presents PACE","authors_text":"Fadi Al Machot, Liyanapathiranage Sudeepika Wajirakumari Samarathunga, Martin Thomas Horsch, Pavel Iakovets","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-01T16:55:06Z","title":"PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.01306","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:a63e604e3186b9bf0f5e61d7e8df8d1229c1d78073cbbb423baf3582e5b3539c","target":"record","created_at":"2026-07-03T00:16:56Z","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":"d472ffbbfa596924e743d67870b7e7f9fc1dc44178d2d3ad3f63967ad643fa46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-01T16:55:06Z","title_canon_sha256":"4225f3c025cfd21906b47eec4ed9d450d4850ac74fe3d432cbabea03fd8c88fb"},"schema_version":"1.0","source":{"id":"2607.01306","kind":"arxiv","version":1}},"canonical_sha256":"3b4211bdf5ed22d6d970e41d55182cf1c0afa5e32d89cdf79cf61bba3a2f4c36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b4211bdf5ed22d6d970e41d55182cf1c0afa5e32d89cdf79cf61bba3a2f4c36","first_computed_at":"2026-07-03T00:16:56.915605Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-03T00:16:56.915605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d0cby7elux/GQB7IbCn0rUIlEVMmR7amLFT2PXOT5aeJw4v2W+dtQoKk+9kUhNmbLmkdPVi62XDymmhP7je8AQ==","signature_status":"signed_v1","signed_at":"2026-07-03T00:16:56.916013Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.01306","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a63e604e3186b9bf0f5e61d7e8df8d1229c1d78073cbbb423baf3582e5b3539c","sha256:fe868de261a75068b3fbe0ea90cad9b5fce83c886d866f6c39f82d020c71c18b"],"state_sha256":"a4f94a874d51bc0e67ac598d12ed1fb5a3e0bb72747b2fd4c960e9cbc36f1e0e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I8IW5NjrZ8u2Qnu/h3M5XrlugGQdYrpCX4bGuMEkXn7/21RZqzNCeD1u7y8r0DUy9N3OTgqaOfx+W5V9X9jxBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T20:02:38.910881Z","bundle_sha256":"7734d583b1e63e77fb970379cd098e82a1ee14759c7eb64bdfa259170bbc3792"}}