{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ECM4SUOCVNTNZY7PABBPFE24P5","short_pith_number":"pith:ECM4SUOC","canonical_record":{"source":{"id":"2504.04945","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-07T11:31:22Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"2747308d62f1d10c760980c854cc90b309f5a824224ed968ec969202dbe46334","abstract_canon_sha256":"65f0c2d9269ae182f60946e5c27d1014fad3da42e50f19d7b33e1e2bec12b37f"},"schema_version":"1.0"},"canonical_sha256":"2099c951c2ab66dce3ef0042f2935c7f48e665a490a66738f76f929519d7b797","source":{"kind":"arxiv","id":"2504.04945","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.04945","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2504.04945v1","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.04945","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"ECM4SUOCVNTN","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"ECM4SUOCVNTNZY7P","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"ECM4SUOC","created_at":"2026-07-05T10:45:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ECM4SUOCVNTNZY7PABBPFE24P5","target":"record","payload":{"canonical_record":{"source":{"id":"2504.04945","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-07T11:31:22Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"2747308d62f1d10c760980c854cc90b309f5a824224ed968ec969202dbe46334","abstract_canon_sha256":"65f0c2d9269ae182f60946e5c27d1014fad3da42e50f19d7b33e1e2bec12b37f"},"schema_version":"1.0"},"canonical_sha256":"2099c951c2ab66dce3ef0042f2935c7f48e665a490a66738f76f929519d7b797","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:45:31.817680Z","signature_b64":"fFvRSq8gKAc05KdeBztu8fdsaMEVqg4XxNz1XFQIvlf3eQkOe2QE6DWp7a30nExR0BuWV+z0vqunpMMElYipCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2099c951c2ab66dce3ef0042f2935c7f48e665a490a66738f76f929519d7b797","last_reissued_at":"2026-07-05T10:45:31.817242Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:45:31.817242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.04945","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":"2026-07-05T10:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ARMAbr1d43vgFJHaolzPYNEjyYW1aCcwDXxttkxrcwxo04r0cpz1RRPyY0orPYjOwrSDnq+Oo+ZYI1U5CfRZBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:23:50.965474Z"},"content_sha256":"c93bde8d6ad34367c056cc84ff1184f4cb592a019144b7b5180ab61a02ce7e6e","schema_version":"1.0","event_id":"sha256:c93bde8d6ad34367c056cc84ff1184f4cb592a019144b7b5180ab61a02ce7e6e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ECM4SUOCVNTNZY7PABBPFE24P5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"Andr\\'e Biedenkapp, Frank Hutter, Noor Awad, Rean Fernandes","submitted_at":"2025-04-07T11:31:22Z","abstract_excerpt":"Legal reasoning tasks present unique challenges for large language models (LLMs) due to the complexity of domain-specific knowledge and reasoning processes. This paper investigates how effectively smaller language models (Llama 2 7B and Llama 3 8B) can be fine-tuned with a limited dataset of 1,514 Multi-state Bar Examination (MBE) questions to improve legal question answering accuracy. We evaluate these models on the 2022 MBE questions licensed from JD Advising, the same dataset used in the 'GPT-4 passes the Bar exam' study. Our methodology involves collecting approximately 200 questions per l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.04945","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/2504.04945/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":"2026-07-05T10:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gwJjm/iA74cGS6EXqL7DpetSBOiv6BEgoIWZu5eW9X9AF0F/zOHAIDqiEaD4EQGlhMr9oGnKq1tyKeQs+nSyAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:23:50.965986Z"},"content_sha256":"f13fed078cefa309247a0e90683472b6e5d39d3b7be5a9282770adb0db524fdc","schema_version":"1.0","event_id":"sha256:f13fed078cefa309247a0e90683472b6e5d39d3b7be5a9282770adb0db524fdc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ECM4SUOCVNTNZY7PABBPFE24P5/bundle.json","state_url":"https://pith.science/pith/ECM4SUOCVNTNZY7PABBPFE24P5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ECM4SUOCVNTNZY7PABBPFE24P5/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":"2026-08-04T12:23:50Z","links":{"resolver":"https://pith.science/pith/ECM4SUOCVNTNZY7PABBPFE24P5","bundle":"https://pith.science/pith/ECM4SUOCVNTNZY7PABBPFE24P5/bundle.json","state":"https://pith.science/pith/ECM4SUOCVNTNZY7PABBPFE24P5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ECM4SUOCVNTNZY7PABBPFE24P5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ECM4SUOCVNTNZY7PABBPFE24P5","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":"65f0c2d9269ae182f60946e5c27d1014fad3da42e50f19d7b33e1e2bec12b37f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-07T11:31:22Z","title_canon_sha256":"2747308d62f1d10c760980c854cc90b309f5a824224ed968ec969202dbe46334"},"schema_version":"1.0","source":{"id":"2504.04945","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.04945","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2504.04945v1","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.04945","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"ECM4SUOCVNTN","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"ECM4SUOCVNTNZY7P","created_at":"2026-07-05T10:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"ECM4SUOC","created_at":"2026-07-05T10:45:31Z"}],"graph_snapshots":[{"event_id":"sha256:f13fed078cefa309247a0e90683472b6e5d39d3b7be5a9282770adb0db524fdc","target":"graph","created_at":"2026-07-05T10:45:31Z","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/2504.04945/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Legal reasoning tasks present unique challenges for large language models (LLMs) due to the complexity of domain-specific knowledge and reasoning processes. This paper investigates how effectively smaller language models (Llama 2 7B and Llama 3 8B) can be fine-tuned with a limited dataset of 1,514 Multi-state Bar Examination (MBE) questions to improve legal question answering accuracy. We evaluate these models on the 2022 MBE questions licensed from JD Advising, the same dataset used in the 'GPT-4 passes the Bar exam' study. Our methodology involves collecting approximately 200 questions per l","authors_text":"Andr\\'e Biedenkapp, Frank Hutter, Noor Awad, Rean Fernandes","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-07T11:31:22Z","title":"A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.04945","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:c93bde8d6ad34367c056cc84ff1184f4cb592a019144b7b5180ab61a02ce7e6e","target":"record","created_at":"2026-07-05T10:45:31Z","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":"65f0c2d9269ae182f60946e5c27d1014fad3da42e50f19d7b33e1e2bec12b37f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-07T11:31:22Z","title_canon_sha256":"2747308d62f1d10c760980c854cc90b309f5a824224ed968ec969202dbe46334"},"schema_version":"1.0","source":{"id":"2504.04945","kind":"arxiv","version":1}},"canonical_sha256":"2099c951c2ab66dce3ef0042f2935c7f48e665a490a66738f76f929519d7b797","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2099c951c2ab66dce3ef0042f2935c7f48e665a490a66738f76f929519d7b797","first_computed_at":"2026-07-05T10:45:31.817242Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:45:31.817242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fFvRSq8gKAc05KdeBztu8fdsaMEVqg4XxNz1XFQIvlf3eQkOe2QE6DWp7a30nExR0BuWV+z0vqunpMMElYipCw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:45:31.817680Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.04945","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c93bde8d6ad34367c056cc84ff1184f4cb592a019144b7b5180ab61a02ce7e6e","sha256:f13fed078cefa309247a0e90683472b6e5d39d3b7be5a9282770adb0db524fdc"],"state_sha256":"c9f72865b9f6382231883ddc85eb540068bdfb3b9b4bb87d52ebec9e222d710b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yk0NJWZQzcoksGHCKROawOttjv0zniiWjf1ZbMDx4dEsaKoHIbGjmdCf8fcLPlfES4dgTkGa+Q9W+TCRViq4DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T12:23:50.971242Z","bundle_sha256":"3683ebc2f3e0db5090bac44a6073ecfdf965d904b1f243a552a278a89276658b"}}