{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:SZXPJRUMQXSQNUSKOHPLNYK2SC","short_pith_number":"pith:SZXPJRUM","schema_version":"1.0","canonical_sha256":"966ef4c68c85e506d24a71deb6e15a90b6aaa977e0bd25bd910d2958067d5821","source":{"kind":"arxiv","id":"2401.15770","version":3},"attestation_state":"computed","paper":{"title":"PILOT: Legal Case Outcome Prediction with Case Law","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Cao Xiao, Jimeng Sun, Lang Cao, Zifeng Wang","submitted_at":"2024-01-28T21:18:05Z","abstract_excerpt":"Machine learning shows promise in predicting the outcome of legal cases, but most research has concentrated on civil law cases rather than case law systems. We identified two unique challenges in making legal case outcome predictions with case law. First, it is crucial to identify relevant precedent cases that serve as fundamental evidence for judges during decision-making. Second, it is necessary to consider the evolution of legal principles over time, as early cases may adhere to different legal contexts. In this paper, we proposed a new framework named PILOT (PredictIng Legal case OuTcome) "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2401.15770","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-28T21:18:05Z","cross_cats_sorted":[],"title_canon_sha256":"b5cd258e55945e70119f9bc80719e783861eca6127aa8806d41c9e67d2fcca89","abstract_canon_sha256":"d684e8c4a5b393c8cf10887512aaeb9288ff81fe7fce89d5d31c5eed90abeb39"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:07:33.327632Z","signature_b64":"cxdHjZkrQhZBcXcPBCA0vTtRhqLV5YAS5J2UKwSh0Up59H+7sp1ZFX3T4lCUJp86J8JCbNRPEW5mZ2WTttHnBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"966ef4c68c85e506d24a71deb6e15a90b6aaa977e0bd25bd910d2958067d5821","last_reissued_at":"2026-07-05T08:07:33.327111Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:07:33.327111Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PILOT: Legal Case Outcome Prediction with Case Law","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Cao Xiao, Jimeng Sun, Lang Cao, Zifeng Wang","submitted_at":"2024-01-28T21:18:05Z","abstract_excerpt":"Machine learning shows promise in predicting the outcome of legal cases, but most research has concentrated on civil law cases rather than case law systems. We identified two unique challenges in making legal case outcome predictions with case law. First, it is crucial to identify relevant precedent cases that serve as fundamental evidence for judges during decision-making. Second, it is necessary to consider the evolution of legal principles over time, as early cases may adhere to different legal contexts. In this paper, we proposed a new framework named PILOT (PredictIng Legal case OuTcome) "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.15770","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/2401.15770/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2401.15770","created_at":"2026-07-05T08:07:33.327175+00:00"},{"alias_kind":"arxiv_version","alias_value":"2401.15770v3","created_at":"2026-07-05T08:07:33.327175+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.15770","created_at":"2026-07-05T08:07:33.327175+00:00"},{"alias_kind":"pith_short_12","alias_value":"SZXPJRUMQXSQ","created_at":"2026-07-05T08:07:33.327175+00:00"},{"alias_kind":"pith_short_16","alias_value":"SZXPJRUMQXSQNUSK","created_at":"2026-07-05T08:07:33.327175+00:00"},{"alias_kind":"pith_short_8","alias_value":"SZXPJRUM","created_at":"2026-07-05T08:07:33.327175+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.24452","citing_title":"Temporal Concept Drift in Legal Judgment Prediction: Neural Baselines Across Three Epochs of Ukrainian Court Decisions","ref_index":2,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC","json":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC.json","graph_json":"https://pith.science/api/pith-number/SZXPJRUMQXSQNUSKOHPLNYK2SC/graph.json","events_json":"https://pith.science/api/pith-number/SZXPJRUMQXSQNUSKOHPLNYK2SC/events.json","paper":"https://pith.science/paper/SZXPJRUM"},"agent_actions":{"view_html":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC","download_json":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC.json","view_paper":"https://pith.science/paper/SZXPJRUM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2401.15770&json=true","fetch_graph":"https://pith.science/api/pith-number/SZXPJRUMQXSQNUSKOHPLNYK2SC/graph.json","fetch_events":"https://pith.science/api/pith-number/SZXPJRUMQXSQNUSKOHPLNYK2SC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC/action/storage_attestation","attest_author":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC/action/author_attestation","sign_citation":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC/action/citation_signature","submit_replication":"https://pith.science/pith/SZXPJRUMQXSQNUSKOHPLNYK2SC/action/replication_record"}},"created_at":"2026-07-05T08:07:33.327175+00:00","updated_at":"2026-07-05T08:07:33.327175+00:00"}