{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:P7LBQK4I2BW7UH5UFIFQKTIGII","short_pith_number":"pith:P7LBQK4I","canonical_record":{"source":{"id":"2502.07912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T19:33:07Z","cross_cats_sorted":[],"title_canon_sha256":"3f9b848855b9338dde1b0b2d5399e36f86817d1f44d9fc704c5277fc1bc3ebf7","abstract_canon_sha256":"454652cf8da2877de9378d9e3fc8ec7653fe8466eaec19424e56aa8750615ed7"},"schema_version":"1.0"},"canonical_sha256":"7fd6182b88d06dfa1fb42a0b054d064237a340dd8fd9f1ae02ad26a0ddffa554","source":{"kind":"arxiv","id":"2502.07912","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.07912","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"arxiv_version","alias_value":"2502.07912v1","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.07912","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_12","alias_value":"P7LBQK4I2BW7","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_16","alias_value":"P7LBQK4I2BW7UH5U","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_8","alias_value":"P7LBQK4I","created_at":"2026-07-05T10:13:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:P7LBQK4I2BW7UH5UFIFQKTIGII","target":"record","payload":{"canonical_record":{"source":{"id":"2502.07912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T19:33:07Z","cross_cats_sorted":[],"title_canon_sha256":"3f9b848855b9338dde1b0b2d5399e36f86817d1f44d9fc704c5277fc1bc3ebf7","abstract_canon_sha256":"454652cf8da2877de9378d9e3fc8ec7653fe8466eaec19424e56aa8750615ed7"},"schema_version":"1.0"},"canonical_sha256":"7fd6182b88d06dfa1fb42a0b054d064237a340dd8fd9f1ae02ad26a0ddffa554","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:13:12.072325Z","signature_b64":"+ytCBk3PQDeSxOaLxWAt2vfww36AqYzVr2vrYA5Ce9j6gxlo6XndcZUSlcjnBfD+xEqejczc4YI8CTOD5K8+Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7fd6182b88d06dfa1fb42a0b054d064237a340dd8fd9f1ae02ad26a0ddffa554","last_reissued_at":"2026-07-05T10:13:12.071898Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:13:12.071898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.07912","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":"2026-07-05T10:13:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2HVXkXua/w4P56G6MdqI1Uf0Tos4PWyuU13uuJhnr/bMlybXq0nJRK70DZEdvOntIzkHL6jIyw8+uteDY4sOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:17:39.532704Z"},"content_sha256":"8c100232e29f4cd5ec4b0aeb3f0bb06bea1a4ec550c018da9a940614fab25c07","schema_version":"1.0","event_id":"sha256:8c100232e29f4cd5ec4b0aeb3f0bb06bea1a4ec550c018da9a940614fab25c07"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:P7LBQK4I2BW7UH5UFIFQKTIGII","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chenghao Wang, Fang Wang, Jingwei Xiong, Rujing Yao, Xiaozhong Liu, Yang Wu","submitted_at":"2025-02-11T19:33:07Z","abstract_excerpt":"Large Language Models (LLMs) have achieved impressive results across numerous domains, yet they experience notable deficiencies in legal question-answering tasks. LLMs often generate generalized responses that lack the logical specificity required for expert legal advice and are prone to hallucination, providing answers that appear correct but are unreliable. Retrieval-Augmented Generation (RAG) techniques offer partial solutions to address this challenge, but existing approaches typically focus only on semantic similarity, neglecting the logical structure essential to legal reasoning. In this"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.07912","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/2502.07912/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":"2026-07-05T10:13:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rd22qV7Er3ZUNkmTo2dTa1BDqdSo+49DwKQYB++DCD3h8TQkeyfo0g0NdbsDDyVPRyTooADrJ34LsVoMwrR/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:17:39.533261Z"},"content_sha256":"3b0412906938812e4c9a5a0c6776ee060d3bc29acae6217962f763483143c5dd","schema_version":"1.0","event_id":"sha256:3b0412906938812e4c9a5a0c6776ee060d3bc29acae6217962f763483143c5dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/bundle.json","state_url":"https://pith.science/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/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":"2026-08-06T00:17:39Z","links":{"resolver":"https://pith.science/pith/P7LBQK4I2BW7UH5UFIFQKTIGII","bundle":"https://pith.science/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/bundle.json","state":"https://pith.science/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P7LBQK4I2BW7UH5UFIFQKTIGII/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:P7LBQK4I2BW7UH5UFIFQKTIGII","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":"454652cf8da2877de9378d9e3fc8ec7653fe8466eaec19424e56aa8750615ed7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T19:33:07Z","title_canon_sha256":"3f9b848855b9338dde1b0b2d5399e36f86817d1f44d9fc704c5277fc1bc3ebf7"},"schema_version":"1.0","source":{"id":"2502.07912","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.07912","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"arxiv_version","alias_value":"2502.07912v1","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.07912","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_12","alias_value":"P7LBQK4I2BW7","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_16","alias_value":"P7LBQK4I2BW7UH5U","created_at":"2026-07-05T10:13:12Z"},{"alias_kind":"pith_short_8","alias_value":"P7LBQK4I","created_at":"2026-07-05T10:13:12Z"}],"graph_snapshots":[{"event_id":"sha256:3b0412906938812e4c9a5a0c6776ee060d3bc29acae6217962f763483143c5dd","target":"graph","created_at":"2026-07-05T10:13:12Z","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/2502.07912/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have achieved impressive results across numerous domains, yet they experience notable deficiencies in legal question-answering tasks. LLMs often generate generalized responses that lack the logical specificity required for expert legal advice and are prone to hallucination, providing answers that appear correct but are unreliable. Retrieval-Augmented Generation (RAG) techniques offer partial solutions to address this challenge, but existing approaches typically focus only on semantic similarity, neglecting the logical structure essential to legal reasoning. In this","authors_text":"Chenghao Wang, Fang Wang, Jingwei Xiong, Rujing Yao, Xiaozhong Liu, Yang Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T19:33:07Z","title":"Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.07912","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":"sha256:8c100232e29f4cd5ec4b0aeb3f0bb06bea1a4ec550c018da9a940614fab25c07","target":"record","created_at":"2026-07-05T10:13:12Z","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":"454652cf8da2877de9378d9e3fc8ec7653fe8466eaec19424e56aa8750615ed7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T19:33:07Z","title_canon_sha256":"3f9b848855b9338dde1b0b2d5399e36f86817d1f44d9fc704c5277fc1bc3ebf7"},"schema_version":"1.0","source":{"id":"2502.07912","kind":"arxiv","version":1}},"canonical_sha256":"7fd6182b88d06dfa1fb42a0b054d064237a340dd8fd9f1ae02ad26a0ddffa554","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7fd6182b88d06dfa1fb42a0b054d064237a340dd8fd9f1ae02ad26a0ddffa554","first_computed_at":"2026-07-05T10:13:12.071898Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:13:12.071898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+ytCBk3PQDeSxOaLxWAt2vfww36AqYzVr2vrYA5Ce9j6gxlo6XndcZUSlcjnBfD+xEqejczc4YI8CTOD5K8+Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:13:12.072325Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.07912","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c100232e29f4cd5ec4b0aeb3f0bb06bea1a4ec550c018da9a940614fab25c07","sha256:3b0412906938812e4c9a5a0c6776ee060d3bc29acae6217962f763483143c5dd"],"state_sha256":"3cbda77de85ff639c0d019aff16bfb45afa5975cf16866f7db6bf5d72f8161d0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7pvi8Qwzn9V7QfE+1eUqcA/VRfiFAefXFYO9B1UWbhWxGtykwXcPKJNFMa9r0y0gLR9VEdbG69zCjm4/j0iHAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T00:17:39.536550Z","bundle_sha256":"8bc84037c02afd96fb21ad32ea7d836e37af84459ade070ae922dda8c865fd45"}}