{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:Z4YQQMH5N3RBUL35TNVJKDBTDR","short_pith_number":"pith:Z4YQQMH5","canonical_record":{"source":{"id":"2311.04348","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-07T21:09:57Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5a6bd566445e743c757e26f7fc38430afa7802724439a56bf13ce1fd8fd0e246","abstract_canon_sha256":"8b0e3aaa73a3917caabb81fd7908d2200abbcb26d9d28283d264eec9c8f77660"},"schema_version":"1.0"},"canonical_sha256":"cf310830fd6ee21a2f7d9b6a950c331c544e212d32509f23a108f51f78367630","source":{"kind":"arxiv","id":"2311.04348","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04348","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04348v1","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04348","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_12","alias_value":"Z4YQQMH5N3RB","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_16","alias_value":"Z4YQQMH5N3RBUL35","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_8","alias_value":"Z4YQQMH5","created_at":"2026-07-05T07:10:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:Z4YQQMH5N3RBUL35TNVJKDBTDR","target":"record","payload":{"canonical_record":{"source":{"id":"2311.04348","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-07T21:09:57Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5a6bd566445e743c757e26f7fc38430afa7802724439a56bf13ce1fd8fd0e246","abstract_canon_sha256":"8b0e3aaa73a3917caabb81fd7908d2200abbcb26d9d28283d264eec9c8f77660"},"schema_version":"1.0"},"canonical_sha256":"cf310830fd6ee21a2f7d9b6a950c331c544e212d32509f23a108f51f78367630","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:10:34.401909Z","signature_b64":"KobP0RFh9fe7GQDMk2zzJQsXB1DvicaKZZOxtB5RDaOEZs9l8n6gpuFx1iqX47pkNLv9S5f0RqOTu9POr49vDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cf310830fd6ee21a2f7d9b6a950c331c544e212d32509f23a108f51f78367630","last_reissued_at":"2026-07-05T07:10:34.401508Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:10:34.401508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.04348","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":"2026-07-05T07:10:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J4RNU1EPz/bp+/VbguVXjzccg+3Ff7VWIa2wdJ7Qj/YwKbOHpq///bzNepfMKPfmZ6y5QYYakzQ+Kb7+yHpTAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:17:45.629801Z"},"content_sha256":"a3475573da0a2f3e49f25c2bf912704163c1daf1b704f06cc92f49cae31427e5","schema_version":"1.0","event_id":"sha256:a3475573da0a2f3e49f25c2bf912704163c1daf1b704f06cc92f49cae31427e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:Z4YQQMH5N3RBUL35TNVJKDBTDR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Anurag Acharya, Sai Munikoti, Sameera Horawalavithana, Sridevi Wagle","submitted_at":"2023-11-07T21:09:57Z","abstract_excerpt":"Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations. Retrieval-augmented LLMs provide a non-parametric approach to solve these issues by retrieving relevant information from external data sources and augment the training process. These models help to trace evidence from an externally provided knowledge base allowing the model predictions to be better interpreted and verified. In this work, we critically evaluate these models in their ability to perform in scientific docu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04348","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/2311.04348/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":"2026-07-05T07:10:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5EKhAiuXsqPCn+dm3sGlgJClY41C4abmjuVJYuI2B5giVL7hgfVqy0fIgVLWbW4n64kmyTx3kakf5tgmgWfnBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:17:45.630626Z"},"content_sha256":"1dcf847c657d9eff89f3e0d21e7bdf5391b0aa693cee9667f3805cafe2e0fb16","schema_version":"1.0","event_id":"sha256:1dcf847c657d9eff89f3e0d21e7bdf5391b0aa693cee9667f3805cafe2e0fb16"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/bundle.json","state_url":"https://pith.science/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/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":"2026-08-09T02:17:45Z","links":{"resolver":"https://pith.science/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR","bundle":"https://pith.science/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/bundle.json","state":"https://pith.science/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z4YQQMH5N3RBUL35TNVJKDBTDR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:Z4YQQMH5N3RBUL35TNVJKDBTDR","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":"8b0e3aaa73a3917caabb81fd7908d2200abbcb26d9d28283d264eec9c8f77660","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-07T21:09:57Z","title_canon_sha256":"5a6bd566445e743c757e26f7fc38430afa7802724439a56bf13ce1fd8fd0e246"},"schema_version":"1.0","source":{"id":"2311.04348","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04348","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04348v1","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04348","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_12","alias_value":"Z4YQQMH5N3RB","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_16","alias_value":"Z4YQQMH5N3RBUL35","created_at":"2026-07-05T07:10:34Z"},{"alias_kind":"pith_short_8","alias_value":"Z4YQQMH5","created_at":"2026-07-05T07:10:34Z"}],"graph_snapshots":[{"event_id":"sha256:1dcf847c657d9eff89f3e0d21e7bdf5391b0aa693cee9667f3805cafe2e0fb16","target":"graph","created_at":"2026-07-05T07:10:34Z","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/2311.04348/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations. Retrieval-augmented LLMs provide a non-parametric approach to solve these issues by retrieving relevant information from external data sources and augment the training process. These models help to trace evidence from an externally provided knowledge base allowing the model predictions to be better interpreted and verified. In this work, we critically evaluate these models in their ability to perform in scientific docu","authors_text":"Anurag Acharya, Sai Munikoti, Sameera Horawalavithana, Sridevi Wagle","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-07T21:09:57Z","title":"Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04348","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:a3475573da0a2f3e49f25c2bf912704163c1daf1b704f06cc92f49cae31427e5","target":"record","created_at":"2026-07-05T07:10:34Z","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":"8b0e3aaa73a3917caabb81fd7908d2200abbcb26d9d28283d264eec9c8f77660","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-07T21:09:57Z","title_canon_sha256":"5a6bd566445e743c757e26f7fc38430afa7802724439a56bf13ce1fd8fd0e246"},"schema_version":"1.0","source":{"id":"2311.04348","kind":"arxiv","version":1}},"canonical_sha256":"cf310830fd6ee21a2f7d9b6a950c331c544e212d32509f23a108f51f78367630","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cf310830fd6ee21a2f7d9b6a950c331c544e212d32509f23a108f51f78367630","first_computed_at":"2026-07-05T07:10:34.401508Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:10:34.401508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KobP0RFh9fe7GQDMk2zzJQsXB1DvicaKZZOxtB5RDaOEZs9l8n6gpuFx1iqX47pkNLv9S5f0RqOTu9POr49vDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:10:34.401909Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.04348","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a3475573da0a2f3e49f25c2bf912704163c1daf1b704f06cc92f49cae31427e5","sha256:1dcf847c657d9eff89f3e0d21e7bdf5391b0aa693cee9667f3805cafe2e0fb16"],"state_sha256":"ca8cbc6bcf33bba10b2c86061eed29332efc298942dc171c23272da41f71676a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fC+YslbTEKjyZ+IgLwhbhuacJAb3gNZQULOaJzbzEyh8Y9ouduQQvzw+OgSUpTFZWxIJ4CeynfIJVCaTvB1WAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T02:17:45.695999Z","bundle_sha256":"edb5d20b8814ffb7a416b2c1225ba227e7d9c351c12e1b2a75cbfd72a869ac89"}}