{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UI7JTZ7B4JTLBECSTGCAKAPC26","short_pith_number":"pith:UI7JTZ7B","schema_version":"1.0","canonical_sha256":"a23e99e7e1e266b0905299840501e2d7ac0e0dd16a1e380d1c4382cceafa7870","source":{"kind":"arxiv","id":"2506.11078","version":1},"attestation_state":"computed","paper":{"title":"RoE-FND: A Case-Based Reasoning Approach with Dual Verification for Fake News Detection via LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Sheng Li, Xinpeng Zhang, Yangming Zhou, Yuzhou Yang, Zhenxing Qian, Zhiying Zhu","submitted_at":"2025-06-04T04:23:58Z","abstract_excerpt":"The proliferation of deceptive content online necessitates robust Fake News Detection (FND) systems. While evidence-based approaches leverage external knowledge to verify claims, existing methods face critical limitations: noisy evidence selection, generalization bottlenecks, and unclear decision-making processes. Recent efforts to harness Large Language Models (LLMs) for FND introduce new challenges, including hallucinated rationales and conclusion bias. To address these issues, we propose \\textbf{RoE-FND} (\\textbf{\\underline{R}}eason \\textbf{\\underline{o}}n \\textbf{\\underline{E}}xperiences F"},"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":"2506.11078","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T04:23:58Z","cross_cats_sorted":[],"title_canon_sha256":"617cf3ab7c31abd1864ffeb91bed9007ec61ea625cab6115d23461d991160e74","abstract_canon_sha256":"ce94ffd79c3484db4ea94a203c639d5a002fc59e6de0858eceefdb955e8b64b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:59.108022Z","signature_b64":"8eVaBuxsBFBp6UNrbT+upjKauGd+ApELyFEIOAhtgHG5F48h9TixzPNrvk4u9mifSbMremp6SJ6vR4qUbJuCAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a23e99e7e1e266b0905299840501e2d7ac0e0dd16a1e380d1c4382cceafa7870","last_reissued_at":"2026-07-05T11:20:59.107615Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:59.107615Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RoE-FND: A Case-Based Reasoning Approach with Dual Verification for Fake News Detection via LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Sheng Li, Xinpeng Zhang, Yangming Zhou, Yuzhou Yang, Zhenxing Qian, Zhiying Zhu","submitted_at":"2025-06-04T04:23:58Z","abstract_excerpt":"The proliferation of deceptive content online necessitates robust Fake News Detection (FND) systems. While evidence-based approaches leverage external knowledge to verify claims, existing methods face critical limitations: noisy evidence selection, generalization bottlenecks, and unclear decision-making processes. Recent efforts to harness Large Language Models (LLMs) for FND introduce new challenges, including hallucinated rationales and conclusion bias. To address these issues, we propose \\textbf{RoE-FND} (\\textbf{\\underline{R}}eason \\textbf{\\underline{o}}n \\textbf{\\underline{E}}xperiences F"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11078","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/2506.11078/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":"2506.11078","created_at":"2026-07-05T11:20:59.107670+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.11078v1","created_at":"2026-07-05T11:20:59.107670+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11078","created_at":"2026-07-05T11:20:59.107670+00:00"},{"alias_kind":"pith_short_12","alias_value":"UI7JTZ7B4JTL","created_at":"2026-07-05T11:20:59.107670+00:00"},{"alias_kind":"pith_short_16","alias_value":"UI7JTZ7B4JTLBECS","created_at":"2026-07-05T11:20:59.107670+00:00"},{"alias_kind":"pith_short_8","alias_value":"UI7JTZ7B","created_at":"2026-07-05T11:20:59.107670+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26","json":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26.json","graph_json":"https://pith.science/api/pith-number/UI7JTZ7B4JTLBECSTGCAKAPC26/graph.json","events_json":"https://pith.science/api/pith-number/UI7JTZ7B4JTLBECSTGCAKAPC26/events.json","paper":"https://pith.science/paper/UI7JTZ7B"},"agent_actions":{"view_html":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26","download_json":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26.json","view_paper":"https://pith.science/paper/UI7JTZ7B","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.11078&json=true","fetch_graph":"https://pith.science/api/pith-number/UI7JTZ7B4JTLBECSTGCAKAPC26/graph.json","fetch_events":"https://pith.science/api/pith-number/UI7JTZ7B4JTLBECSTGCAKAPC26/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26/action/storage_attestation","attest_author":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26/action/author_attestation","sign_citation":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26/action/citation_signature","submit_replication":"https://pith.science/pith/UI7JTZ7B4JTLBECSTGCAKAPC26/action/replication_record"}},"created_at":"2026-07-05T11:20:59.107670+00:00","updated_at":"2026-07-05T11:20:59.107670+00:00"}