{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:OYMRVK4MK2NZNRNCXL5ZOXTW56","short_pith_number":"pith:OYMRVK4M","canonical_record":{"source":{"id":"2505.01482","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-02T16:16:17Z","cross_cats_sorted":[],"title_canon_sha256":"48ea156495bf4dc45da89d6caae2fe1d01eebd6411077dd605939a63f0f6ef95","abstract_canon_sha256":"be84d3642f1bc695245ef2a9c5a26cc7be50e684301fc71cf7e97ac2421dd976"},"schema_version":"1.0"},"canonical_sha256":"76191aab8c569b96c5a2bafb975e76efbd3a92bc9477baa91f5cdfb0a49d31da","source":{"kind":"arxiv","id":"2505.01482","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.01482","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"arxiv_version","alias_value":"2505.01482v2","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.01482","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_12","alias_value":"OYMRVK4MK2NZ","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_16","alias_value":"OYMRVK4MK2NZNRNC","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_8","alias_value":"OYMRVK4M","created_at":"2026-07-05T11:43:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:OYMRVK4MK2NZNRNCXL5ZOXTW56","target":"record","payload":{"canonical_record":{"source":{"id":"2505.01482","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-02T16:16:17Z","cross_cats_sorted":[],"title_canon_sha256":"48ea156495bf4dc45da89d6caae2fe1d01eebd6411077dd605939a63f0f6ef95","abstract_canon_sha256":"be84d3642f1bc695245ef2a9c5a26cc7be50e684301fc71cf7e97ac2421dd976"},"schema_version":"1.0"},"canonical_sha256":"76191aab8c569b96c5a2bafb975e76efbd3a92bc9477baa91f5cdfb0a49d31da","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:11.724355Z","signature_b64":"0o/PukPQ9Y3nB03c7ymXZUZONU/4FHelimrrcMPu/VgbJ8QrsHc4rLBULlmUjC70kx8ZcNmAN0cFYlDQqMVZCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"76191aab8c569b96c5a2bafb975e76efbd3a92bc9477baa91f5cdfb0a49d31da","last_reissued_at":"2026-07-05T11:43:11.723667Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:11.723667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.01482","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:43:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"daTZTlErFOQklksn45Ed1ElA0Gtp60Gp+HAS/KvB9VxzDLw6qo7Y7+4IU6sS1IHQjEGHq2U1nK6Fu4o7+ts8AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T07:46:45.112674Z"},"content_sha256":"5fd4577cd24835657ce3322d1885790532bcd160f2814c0e47c45d72c621e57b","schema_version":"1.0","event_id":"sha256:5fd4577cd24835657ce3322d1885790532bcd160f2814c0e47c45d72c621e57b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:OYMRVK4MK2NZNRNCXL5ZOXTW56","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding LLM Scientific Reasoning through Promptings and Model's Explanation on the Answers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Alice Rueda, Argyrios Perivolaris, Bazen G. Teferra, Bo Cao, Divya Sharma, Mohammed S. Hassan, Reza Samavi, Sirisha Rambhatla, Sridhar Krishnan, Venkat Bhat, Yanbo Zhang, Yuqi Wu","submitted_at":"2025-05-02T16:16:17Z","abstract_excerpt":"Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and problem-solving across various domains. However, their ability to perform complex, multi-step reasoning task-essential for applications in science, medicine, and law-remains an area of active investigation. This paper examines the reasoning capabilities of contemporary LLMs, analyzing their strengths, limitations, and potential for improvement. The study uses prompt engineering techniques on the Graduate-Level GoogleProof Q&A (GPQA) dataset to assess the scientific reasoning"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.01482","kind":"arxiv","version":2},"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/2505.01482/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":"2026-07-05T11:43:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1bSXe2NJ7nlfP1cTBIWVvGtaN/ER3Z9FzmUuaL7Ju4/ZGHfTbvErIloqAMVfmUdg9O3xtLwe9ijnVHqMgOaDDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T07:46:45.113517Z"},"content_sha256":"7f6261087505047bd943960ed097c6b5d4df4d7b13139a7353390e28ae933551","schema_version":"1.0","event_id":"sha256:7f6261087505047bd943960ed097c6b5d4df4d7b13139a7353390e28ae933551"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/bundle.json","state_url":"https://pith.science/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/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":"2026-08-22T07:46:45Z","links":{"resolver":"https://pith.science/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56","bundle":"https://pith.science/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/bundle.json","state":"https://pith.science/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OYMRVK4MK2NZNRNCXL5ZOXTW56/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OYMRVK4MK2NZNRNCXL5ZOXTW56","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":"be84d3642f1bc695245ef2a9c5a26cc7be50e684301fc71cf7e97ac2421dd976","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-02T16:16:17Z","title_canon_sha256":"48ea156495bf4dc45da89d6caae2fe1d01eebd6411077dd605939a63f0f6ef95"},"schema_version":"1.0","source":{"id":"2505.01482","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.01482","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"arxiv_version","alias_value":"2505.01482v2","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.01482","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_12","alias_value":"OYMRVK4MK2NZ","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_16","alias_value":"OYMRVK4MK2NZNRNC","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_8","alias_value":"OYMRVK4M","created_at":"2026-07-05T11:43:11Z"}],"graph_snapshots":[{"event_id":"sha256:7f6261087505047bd943960ed097c6b5d4df4d7b13139a7353390e28ae933551","target":"graph","created_at":"2026-07-05T11:43:11Z","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/2505.01482/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and problem-solving across various domains. However, their ability to perform complex, multi-step reasoning task-essential for applications in science, medicine, and law-remains an area of active investigation. This paper examines the reasoning capabilities of contemporary LLMs, analyzing their strengths, limitations, and potential for improvement. The study uses prompt engineering techniques on the Graduate-Level GoogleProof Q&A (GPQA) dataset to assess the scientific reasoning","authors_text":"Alice Rueda, Argyrios Perivolaris, Bazen G. Teferra, Bo Cao, Divya Sharma, Mohammed S. Hassan, Reza Samavi, Sirisha Rambhatla, Sridhar Krishnan, Venkat Bhat, Yanbo Zhang, Yuqi Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-02T16:16:17Z","title":"Understanding LLM Scientific Reasoning through Promptings and Model's Explanation on the Answers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.01482","kind":"arxiv","version":2},"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":"sha256:5fd4577cd24835657ce3322d1885790532bcd160f2814c0e47c45d72c621e57b","target":"record","created_at":"2026-07-05T11:43:11Z","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":"be84d3642f1bc695245ef2a9c5a26cc7be50e684301fc71cf7e97ac2421dd976","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-02T16:16:17Z","title_canon_sha256":"48ea156495bf4dc45da89d6caae2fe1d01eebd6411077dd605939a63f0f6ef95"},"schema_version":"1.0","source":{"id":"2505.01482","kind":"arxiv","version":2}},"canonical_sha256":"76191aab8c569b96c5a2bafb975e76efbd3a92bc9477baa91f5cdfb0a49d31da","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"76191aab8c569b96c5a2bafb975e76efbd3a92bc9477baa91f5cdfb0a49d31da","first_computed_at":"2026-07-05T11:43:11.723667Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:11.723667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0o/PukPQ9Y3nB03c7ymXZUZONU/4FHelimrrcMPu/VgbJ8QrsHc4rLBULlmUjC70kx8ZcNmAN0cFYlDQqMVZCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:11.724355Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.01482","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5fd4577cd24835657ce3322d1885790532bcd160f2814c0e47c45d72c621e57b","sha256:7f6261087505047bd943960ed097c6b5d4df4d7b13139a7353390e28ae933551"],"state_sha256":"46a4840bbfe36818c352e0027fdf27b672799cc745b2ed8cf1fee0d65f0dce19"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VF8aGuvgJ6F6EnWKjog4rIAOePjgsKC90jDfk1jfCw0CBLX2+8WhIIlAMI4jlgb3DGBWOWgYVzCjIDRHO7vVAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T07:46:45.120377Z","bundle_sha256":"15fc910be156b6bb1d3be0c789d2c5f406d125da4b3754e3cc016933cb96a276"}}