{"as_of":"2026-08-16T11:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52c38276437c3126f9b7901230572a92d90c520a9fc7af4a49b77d4fedd8e5e6","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:29:50.523585Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.04680/citation-record","integrity":"/paper/2505.04680/integrity","json":"/paper/2505.04680/citation-record.json","paper":"/paper/2505.04680"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.268801Z","title":"Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.268801Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:028cdbfa926f6dae54ee8b5f0d710171e4cf987c6aa26d90d2341e3b1cd438b2","observation_id":"6c1547c6-b134-4c85-8881-7128511cbbce","resolution":{"observed_at":"2026-08-15T23:29:50.268801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-14T10:40:26.323157Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-15T23:29:50.274254Z","title":"A Survey of Large Language Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.274254Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:16137435078f3f9e247160c9efcd9d5054e01898df93c87434cef9fe86cd76cc","observation_id":"6a243e49-d131-449b-b0ae-e67e325dbecc","resolution":{"observed_at":"2026-08-15T23:29:50.274254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.279970Z","title":"Large language models in medicine,","venue":null,"work_id":null,"year":1930},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.279970Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:44e56bd5f3dd57013431c74d9d372db6f87d5e34b90a29f0952e1b8cb4577529","observation_id":"1a0ca7cf-4d0c-40ee-bdd9-611ed67db173","resolution":{"observed_at":"2026-08-15T23:29:50.279970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.06435","last_updated":"2024-10-17T01:10:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-12T20:01:52Z","title":"A Comprehensive Overview of Large Language Models","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.06435","snapshot_observed_at":"2026-08-15T23:29:50.284570Z","title":"A Comprehensive Overview of Large Language Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.284570Z"},"links":{"cited_paper":"/paper/2307.06435","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:a0f9415da90fce5eb7197ecda7e46b90657b0e44fd7106e196db0270ae76e25c","observation_id":"faec1aa8-3549-4c47-a604-241db09635cd","resolution":{"observed_at":"2026-08-15T23:29:50.284570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.04554","last_updated":"2021-06-15T07:56:19Z","snapshot_observed_at":"2026-08-15T05:45:34.556135Z","submitted_at":"2021-06-08T17:43:08Z","title":"A Survey of Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.04554","snapshot_observed_at":"2026-08-15T23:29:50.289725Z","title":"A Survey of Transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.289725Z"},"links":{"cited_paper":"/paper/2106.04554","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:63acaf45de63db721bbd5ce596798f4fb2f490dedcc39a0f966fb776c002e2e2","observation_id":"6f402145-8279-4916-8160-894f4767b8a8","resolution":{"observed_at":"2026-08-15T23:29:50.289725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-08-16T05:25:19.960199Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-15T23:29:50.294231Z","title":"Attention Is All You Need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.294231Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:336121b7539d9c794b8421119aab3001f5729ef9af8eb2303c668559ec674975","observation_id":"40fc1a6c-949d-4c90-a9b1-8957e854f7cf","resolution":{"observed_at":"2026-08-15T23:29:50.294231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-15T23:29:50.299571Z","title":"Language Models are Few -Shot Learners,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.299571Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:77b48391abc67f40b15ef9a4805687efcbfbe1a17de114943c82565abda138f0","observation_id":"419e74a4-936b-4809-8e88-65e8de4cbac2","resolution":{"observed_at":"2026-08-15T23:29:50.299571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.303801Z","title":"A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.303801Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:9642ab9711ad2baf78c9ce9b73938a8bdef22163fe694563abe6ee8b54d36fe5","observation_id":"ff4a91d3-33e1-4b71-8d2b-11ea794ddb99","resolution":{"observed_at":"2026-08-15T23:29:50.303801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.308198Z","title":"Analyzing Leakage of Personally Identifiable Information in Language Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.308198Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:a546e01d230cce5e88f8264b0ed1334c98ed97a3a47f1ba3f2c33d66a60880a0","observation_id":"b0745f95-d6b5-452b-9661-772f369c70d9","resolution":{"observed_at":"2026-08-15T23:29:50.308198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.12628","last_updated":"2022-10-20T05:30:43Z","snapshot_observed_at":"2026-08-13T15:37:25.265059Z","submitted_at":"2022-05-25T10:08:45Z","title":"Are Large Pre-Trained Language Models Leaking Your Personal Information?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.12628","snapshot_observed_at":"2026-08-15T23:29:50.312208Z","title":"Are Large Pre -Trained Language Models Leaking Your Personal Information?,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.312208Z"},"links":{"cited_paper":"/paper/2205.12628","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:005c1af59d23884a5a15e347ca22622ed1d3fcb81642aff82a77ce12e84ad478","observation_id":"082ac750-8a8b-4026-b52a-91f125d59041","resolution":{"observed_at":"2026-08-15T23:29:50.312208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.316480Z","title":"Bias and Fairness in Lar ge Language Models: A Survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.316480Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:68c868d2bed84283bc46188da58ec045d827c709ac4fcbd69e2fe6a924329c1f","observation_id":"f404674a-68a2-4910-b2e6-c53555f035d9","resolution":{"observed_at":"2026-08-15T23:29:50.316480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.320543Z","title":"Explainability for Large Language Models: A Survey,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.320543Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:306c6e460bec451ca2b5e9f28fb8a8c1c3867849c2a1b6043cf0d8a92cfbf257","observation_id":"606c45d2-723f-4293-84b3-2ecfed18f989","resolution":{"observed_at":"2026-08-15T23:29:50.320543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01761","last_updated":"2024-01-30T17:38:54Z","snapshot_observed_at":"2026-08-16T02:42:51.457352Z","submitted_at":"2024-01-30T17:38:54Z","title":"Rethinking Interpretability in the Era of Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01761","snapshot_observed_at":"2026-08-15T23:29:50.325552Z","title":"Rethinking Interpretability in the Era of Large Language Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.325552Z"},"links":{"cited_paper":"/paper/2402.01761","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:4d3b34ccbf6296dab4f9251c75db5cbc26bdaf60d27bf981815ad385b265067f","observation_id":"f122cbc2-dcbe-46f2-925c-bbbae5c8e79e","resolution":{"observed_at":"2026-08-15T23:29:50.325552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.01219","last_updated":"2025-09-14T09:34:46Z","snapshot_observed_at":"2026-07-06T16:13:46.112815Z","submitted_at":"2023-09-03T16:56:48Z","title":"Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.01219","snapshot_observed_at":"2026-08-15T23:29:50.330044Z","title":"Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.330044Z"},"links":{"cited_paper":"/paper/2309.01219","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:5dc77575fc5ac1fb3631f41c483131654e488acc815a1d0420322ab5cff66bcc","observation_id":"fd3d8392-03de-42da-9716-43b5e4af9a07","resolution":{"observed_at":"2026-08-15T23:29:50.330044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.11462","last_updated":"2020-09-25T20:22:26Z","snapshot_observed_at":"2026-08-09T05:10:26.091710Z","submitted_at":"2020-09-24T03:17:19Z","title":"RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.11462","snapshot_observed_at":"2026-08-15T23:29:50.334832Z","title":"RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.334832Z"},"links":{"cited_paper":"/paper/2009.11462","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:37a64cf55152806f6d405dbffe9caf69526eb10b92c563a515fdd0e79b438664","observation_id":"e34c1222-9e42-4d00-ac71-72f13a55bbad","resolution":{"observed_at":"2026-08-15T23:29:50.334832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.339006Z","title":"The long but necessary road to responsible use of large language models in healthcare research,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.339006Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:ed54e9c39fe8e0a598a482b40ede02952a5da27bd9b04984b85ec310cfd25adc","observation_id":"d2dcde57-03b0-4103-b706-00956ceb4904","resolution":{"observed_at":"2026-08-15T23:29:50.339006Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.604779Z","title":"Communication-Efficient Learning of Deep Networks f rom Decentralized Data,","venue":null,"work_id":"05fb56d5-8de5-4489-869d-a09f94999744","year":2017},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.343461Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:39e167ffa549db042a891a5f87862b3cd67b0aecb147f4765e63222c47469065","observation_id":"0af9ad42-9d63-499f-99ae-49bf85bc0c19","resolution":{"observed_at":"2026-08-15T23:29:51.608928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.06963","last_updated":"2018-02-24T00:40:30Z","snapshot_observed_at":"2026-08-14T20:22:22.512463Z","submitted_at":"2017-10-18T23:46:57Z","title":"Learning Differentially Private Recurrent Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.06963","snapshot_observed_at":"2026-08-15T23:29:50.348174Z","title":"Learning Differentially Private Recurrent Language Models,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.348174Z"},"links":{"cited_paper":"/paper/1710.06963","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:72aab91d1d36019ec3fb4856dbf3df3453b99dbc640c4f37a2b5845642a58af3","observation_id":"e06c7ad5-78ad-4453-b087-0e78bdc938ec","resolution":{"observed_at":"2026-08-15T23:29:50.348174Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.352632Z","title":"The Algorithmic Foundations of Differential P rivacy,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.352632Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:e14a407cc0e7288fc6bf75b746f7deadfd99f6e97502c74c39978c14b3cb2e0d","observation_id":"588a8f7e-a580-4fa6-bfb3-28e69ff9465e","resolution":{"observed_at":"2026-08-15T23:29:50.352632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.356831Z","title":"A Survey on Bias and Fairness in Machine Learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.356831Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:d946344926349b339ce0d478fc55b03e06a0a5aa669852c7bc9981bd74ce4c9f","observation_id":"604f7ca5-e75d-4c65-b123-fbdd9dc936ff","resolution":{"observed_at":"2026-08-15T23:29:50.356831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.361837Z","title":"‘Why Should I Trust You?’: Explaining the Predictions of Any Classifier,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.361837Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:cefb5016bad2c4f6f5019b7f6914749ed4bba7ec720f368838a52221e8743702","observation_id":"02b58394-87cf-4b30-8b18-e1c7b40b9d84","resolution":{"observed_at":"2026-08-15T23:29:50.361837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1606.05386","last_updated":"2016-06-16T23:39:41Z","snapshot_observed_at":"2026-08-15T02:18:02.092001Z","submitted_at":"2016-06-16T23:39:41Z","title":"Model-Agnostic Interpretability of Machine Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.05386","snapshot_observed_at":"2026-08-15T23:29:50.365934Z","title":"Model-Agnostic Interpretability of Machine Learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.365934Z"},"links":{"cited_paper":"/paper/1606.05386","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:36482c5809d6aa2072a67c8c288808acf70dd9a8c8f65d740f7c88cfbcea0629","observation_id":"e4d3b7b1-5645-482a-81d9-de0329be86c9","resolution":{"observed_at":"2026-08-15T23:29:50.365934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.592334Z","title":"A Unified Approach to Interpreting Model Predictions,","venue":null,"work_id":"a2f33270-b09c-4f1f-83ee-9c23ffcc4e37","year":2017},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.370594Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:e2f17d279419ad533a1dde72d53b9b68af5b3ea88c4cf5ed463cc0a25750bdca","observation_id":"98bb19cc-5284-4053-8740-89afd3d2a7f6","resolution":{"observed_at":"2026-08-15T23:29:51.596431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.578525Z","title":"Retrieval -Augmented Generation for Knowledge -Intensive NLP Tasks,","venue":null,"work_id":"81677f37-a1dc-4fa1-8b01-b13e63a65398","year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.374455Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:51b9743826e542ea02624a06f699520d9c13c39b8c3baf532197ad7281d299b4","observation_id":"474a6f0a-a61e-4b97-ae73-90500ee45779","resolution":{"observed_at":"2026-08-15T23:29:51.583423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08787","last_updated":"2024-12-06T21:39:49Z","snapshot_observed_at":"2026-08-14T03:11:49.519597Z","submitted_at":"2024-02-13T20:51:58Z","title":"Rethinking Machine Unlearning for Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.08787","snapshot_observed_at":"2026-08-15T23:29:50.378790Z","title":"Rethinking Machine Unlearning for Large Language Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.378790Z"},"links":{"cited_paper":"/paper/2402.08787","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:7c83f129d4dbf33a5ee8247de48b38432bc141594422502ed248b5828d50365f","observation_id":"81f69686-9de3-498a-a770-236df717e67a","resolution":{"observed_at":"2026-08-15T23:29:50.378790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06674","last_updated":"2023-12-07T19:40:50Z","snapshot_observed_at":"2026-08-14T15:42:19.849118Z","submitted_at":"2023-12-07T19:40:50Z","title":"Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06674","snapshot_observed_at":"2026-08-15T23:29:50.383497Z","title":"Llama Guard: LLM -based Input-Output Safeguard for Human -AI Conversations,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.383497Z"},"links":{"cited_paper":"/paper/2312.06674","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:9477d6f63c92d19a72a17f2ec6846cc44363b709ec0f46b5287e3c65790e9ee5","observation_id":"2a26926d-d4e4-408a-8401-c85f69bb37d5","resolution":{"observed_at":"2026-08-15T23:29:50.383497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.09731","last_updated":"2023-05-16T18:05:19Z","snapshot_observed_at":"2026-08-14T12:25:45.254399Z","submitted_at":"2023-05-16T18:05:19Z","title":"What In-Context Learning \"Learns\" In-Context: Disentangling Task Recognition and Task Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.09731","snapshot_observed_at":"2026-08-15T23:29:50.387867Z","title":"What In -Context Learning ‘Learns’ In - Context: Disentangling Task Recognition and Task Learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.387867Z"},"links":{"cited_paper":"/paper/2305.09731","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:3dd3309c4b32ebb1cdaf1a41b61f4a8ddb5ca125f28d7658717e10cde59d1d5a","observation_id":"a512c59e-12d2-4af8-a4f2-34845cc5abac","resolution":{"observed_at":"2026-08-15T23:29:50.387867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16938","last_updated":"2023-05-30T08:34:49Z","snapshot_observed_at":"2026-08-13T11:32:26.132132Z","submitted_at":"2023-05-26T13:55:17Z","title":"Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16938","snapshot_observed_at":"2026-08-15T23:29:50.392949Z","title":"Few -shot Fine- tuning vs. In -context Learning: A Fair Comparison and Evaluation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.392949Z"},"links":{"cited_paper":"/paper/2305.16938","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:2e036e28b70900434e473cb68a52b49085269be7c9fe211845d3f76ecd510867","observation_id":"5d7f509a-0c7b-46a3-a8ee-2a9b7e9b4dbf","resolution":{"observed_at":"2026-08-15T23:29:50.392949Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.563558Z","title":"Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning,","venue":null,"work_id":"a3d7bb6a-b5e2-4e6d-a2be-17195cf74ebb","year":1950},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.397288Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:0a54860ecfb29e8b9c59d6432fff14fd9ee1d172d893969c994d9f731724b3a7","observation_id":"665aa0c5-5e51-42fb-9017-f5dbf9c41a6c","resolution":{"observed_at":"2026-08-15T23:29:51.568479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.48550/arxiv.2402.12819","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.846847Z","title":"Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break- Even Performance,","venue":null,"work_id":"84032081-8474-4fc4-b1d9-4151161d63dd","year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.401281Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:0b979628bb6ea570230731c9bc84b8d71f13f5a2778e167056c14ddc8c55ed5c","observation_id":"ac2e771f-61b6-4b01-a451-00f3433f8e13","resolution":{"observed_at":"2026-08-15T23:29:50.853039Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.12307","last_updated":"2024-03-08T15:26:38Z","snapshot_observed_at":"2026-08-13T10:08:08.030837Z","submitted_at":"2023-09-21T17:59:11Z","title":"LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.12307","snapshot_observed_at":"2026-08-15T23:29:50.405430Z","title":"LongLoRA: Efficient Fine -tuning of Long -Context Large Language Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.405430Z"},"links":{"cited_paper":"/paper/2309.12307","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:691811b79900d778df459e3f81510395fd9a6fedb2ec0c4d5ec75c4acfd04f71","observation_id":"c6dbefa3-7ad7-4f4c-88cc-62c988a2f792","resolution":{"observed_at":"2026-08-15T23:29:50.405430Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-15T23:29:50.410607Z","title":"Retrieval -Augmented Generation for Large Language Models: A Survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.410607Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:bc9acd553e3a2bd5451ff684ad6f2a38725e2f7723300e4a6dce89f60389c078","observation_id":"4db46fe8-ff2a-4d50-ab37-863a157542f1","resolution":{"observed_at":"2026-08-15T23:29:50.410607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.19473","last_updated":"2024-06-21T08:26:36Z","snapshot_observed_at":"2026-08-13T05:27:55.126585Z","submitted_at":"2024-02-29T18:59:01Z","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.19473","snapshot_observed_at":"2026-08-15T23:29:50.415605Z","title":"Retrieval -Augmented Generation for AI -Generated Content: A Survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.415605Z"},"links":{"cited_paper":"/paper/2402.19473","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:7b566a9c26dc31161562fb9e7ba74c1f3973acc8c832c8882a890a4fe7ba1707","observation_id":"4dec94a0-0189-43b3-a84b-23355556cd30","resolution":{"observed_at":"2026-08-15T23:29:50.415605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.550611Z","title":"Evaluating the Ideal Chunk Size for a RAG System using LlamaIndex — LlamaIndex, Data Framework for LLM Applications","venue":null,"work_id":"97a44319-5efd-4028-9dd4-9d89e71ac775","year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.419977Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:7c60a737f5f0e34ba1ebd590f660a1ed0018f0f0fec402c83c656ef13560d2a6","observation_id":"e34a5c57-5be9-45ad-9334-0bd053b188e0","resolution":{"observed_at":"2026-08-15T23:29:51.554941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.536987Z","title":"Recursively split by character | 🦜️🦜️ LangChain","venue":null,"work_id":"44f6a884-3bd9-46f6-8368-ac1129f9c44e","year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.424064Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:d8bca5b7200bd797d8ad541bb41a408c628d2363d0358533c2d05e15b5c6a759","observation_id":"f7b45622-4cda-47b9-b3c2-0bd1d6e3c056","resolution":{"observed_at":"2026-08-15T23:29:51.541068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11730","last_updated":"2023-12-25T17:03:05Z","snapshot_observed_at":"2026-08-13T10:29:28.165504Z","submitted_at":"2023-08-22T18:41:31Z","title":"Knowledge Graph Prompting for Multi-Document Question Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11730","snapshot_observed_at":"2026-08-15T23:29:50.428185Z","title":"Knowledge Graph Prompting for Multi -Document Question Answering,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.428185Z"},"links":{"cited_paper":"/paper/2308.11730","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:f6be60bc64e26da6a6c03536f8fae86bfe513afbbfb2ce7f80f598089880e0b4","observation_id":"b94ecc48-a6bb-4a22-b89b-24c1c9ed6046","resolution":{"observed_at":"2026-08-15T23:29:50.428185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.523505Z","title":"Distributed Representations of Words and Phrases and their Compositionality,","venue":null,"work_id":"82941654-ae47-42d9-bfc5-7d48cdc30749","year":2013},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.432276Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:ec2021754d7b3871a2ddcbfa89edd13e6eaa6f1fd37b89973dce5621d52785d7","observation_id":"600a0f87-46ae-4c3b-b8d6-b3453ab11a3e","resolution":{"observed_at":"2026-08-15T23:29:51.527810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-15T23:29:50.436192Z","title":"BERT: Pre -training of Deep Bidirectional Transformers for Language Understanding,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.436192Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:f71d8c45fc02e1773d345caac8c6fdd974688c15bd700de298883c1eb13a6028","observation_id":"b96bd143-d3c7-45ed-86e3-3f645ff3b313","resolution":{"observed_at":"2026-08-15T23:29:50.436192Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10225","last_updated":"2024-10-30T02:58:14Z","snapshot_observed_at":"2026-08-15T13:16:17.400983Z","submitted_at":"2024-01-18T18:59:11Z","title":"ChatQA: Surpassing GPT-4 on Conversational QA and RAG","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10225","snapshot_observed_at":"2026-08-15T23:29:50.441306Z","title":"ChatQA: Surpassing GPT-4 on Conversational QA and RAG,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.441306Z"},"links":{"cited_paper":"/paper/2401.10225","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:7ba65db6f2924c76fd56c4aa4f3b9875c7a459e8df7a77ee89f398b29f7494ed","observation_id":"63a10281-8989-450a-8571-f4c4baea082b","resolution":{"observed_at":"2026-08-15T23:29:50.441306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08909","last_updated":"2020-02-10T18:40:59Z","snapshot_observed_at":"2026-08-02T17:52:27.326803Z","submitted_at":"2020-02-10T18:40:59Z","title":"REALM: Retrieval-Augmented Language Model Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08909","snapshot_observed_at":"2026-08-15T23:29:50.445580Z","title":"REALM: Retrieval - Augmented Language Model Pre -Training,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.445580Z"},"links":{"cited_paper":"/paper/2002.08909","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:6ca7ea93fe153812643a0a4a704c042dc575a2fcaa41ad9d1382c33de87f2789","observation_id":"be7766a3-50f8-4c03-8a0c-006b0bf3ad35","resolution":{"observed_at":"2026-08-15T23:29:50.445580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.12652","last_updated":"2023-05-24T05:08:07Z","snapshot_observed_at":"2026-08-02T02:08:12.414817Z","submitted_at":"2023-01-30T04:18:09Z","title":"REPLUG: Retrieval-Augmented Black-Box Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.12652","snapshot_observed_at":"2026-08-15T23:29:50.450847Z","title":"REPLUG: Retrieval -Augmented Black-Box Language Models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.450847Z"},"links":{"cited_paper":"/paper/2301.12652","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:5f05fd7780cf27572c6b31db226deb4b5606e2364b2be889c9c86a858518efaa","observation_id":"0bf07b70-0081-4afd-8179-31ee1adfb053","resolution":{"observed_at":"2026-08-15T23:29:50.450847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07713","last_updated":"2024-05-29T04:15:39Z","snapshot_observed_at":"2026-08-16T01:41:27.164198Z","submitted_at":"2023-10-11T17:59:05Z","title":"InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07713","snapshot_observed_at":"2026-08-15T23:29:50.455307Z","title":"InstructRetro: Instruction Tuning post Retrieval -Augmented Pretraining,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.455307Z"},"links":{"cited_paper":"/paper/2310.07713","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:68894a78ef70d1af8849749d9462748bb161da5a330f755b16d66b0c59bd5c85","observation_id":"ce1f2fd0-781e-4e79-bcde-692ba4a06094","resolution":{"observed_at":"2026-08-15T23:29:50.455307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1301.3781","last_updated":"2013-09-07T00:30:40Z","snapshot_observed_at":"2026-07-06T03:04:11.148340Z","submitted_at":"2013-01-16T18:24:43Z","title":"Efficient Estimation of Word Representations in Vector Space","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1301.3781","snapshot_observed_at":"2026-08-15T23:29:50.460340Z","title":"Efficient Estimation of Word Representations in Vector Space,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.460340Z"},"links":{"cited_paper":"/paper/1301.3781","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:58389945c66a5aa43d0b2b0a75ce567cc5956030c0e249484f73900e61c7d1c7","observation_id":"3787c558-a974-485f-889d-a86eb95fadb8","resolution":{"observed_at":"2026-08-15T23:29:50.460340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:50.464816Z","title":"GloVe: Global Vectors for Word Representation,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.464816Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:b9e6d2bcadb2d1ce1470af0ea2f1035b0f4232ba6cdc09bd690b4ea4cc20d5eb","observation_id":"25d50daa-52e9-48d5-be3a-274b7ccd7a0a","resolution":{"observed_at":"2026-08-15T23:29:50.464816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10084","last_updated":"2019-08-27T08:50:17Z","snapshot_observed_at":"2026-08-14T05:02:11.716316Z","submitted_at":"2019-08-27T08:50:17Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10084","snapshot_observed_at":"2026-08-15T23:29:50.469891Z","title":"Sentence -BERT: Sentence Embeddings using Siamese BERT -Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.469891Z"},"links":{"cited_paper":"/paper/1908.10084","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:e3eb41310c288d791dfbcd4cd343af9c59e74f9f5b42dbdee4e1135f1a3731c4","observation_id":"c69971a4-b936-47c1-bde4-1ea7abd28c13","resolution":{"observed_at":"2026-08-15T23:29:50.469891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00368","last_updated":"2024-05-31T07:22:01Z","snapshot_observed_at":"2026-08-16T10:45:57.265598Z","submitted_at":"2023-12-31T02:13:18Z","title":"Improving Text Embeddings with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.00368","snapshot_observed_at":"2026-08-15T23:29:50.474156Z","title":"[2401.00368] Improving Text Embeddings with Large Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.474156Z"},"links":{"cited_paper":"/paper/2401.00368","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:ebd7b9b37ba56c8035587afc2f758a686bc7ac0a413ca9b64374034c92766e61","observation_id":"e312e2ef-f8cc-4e78-b3d5-2d551cc96435","resolution":{"observed_at":"2026-08-15T23:29:50.474156Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-15T23:29:50.479129Z","title":"Mistral 7B,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.479129Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:b613e71b87cbc81d871b89d1d0c0e91cd33802e771f0be3d0c469f42b9f75f2d","observation_id":"ccb39d48-4692-4978-b85a-9f4baef63ec7","resolution":{"observed_at":"2026-08-15T23:29:50.479129Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07316","last_updated":"2023-03-19T13:37:01Z","snapshot_observed_at":"2026-08-14T05:00:07.792972Z","submitted_at":"2022-10-13T19:42:08Z","title":"MTEB: Massive Text Embedding Benchmark","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07316","snapshot_observed_at":"2026-08-15T23:29:50.483509Z","title":"MTEB: Massive Text Embedding Benchmark,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.483509Z"},"links":{"cited_paper":"/paper/2210.07316","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:8385ac0885ad3654f18574998b6973c798f22f9bfa9551ad715f98891fe639a1","observation_id":"5f43a1c1-880d-4073-8537-8a5cd0a9bb6c","resolution":{"observed_at":"2026-08-15T23:29:50.483509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05961","last_updated":"2024-08-21T22:46:05Z","snapshot_observed_at":"2026-08-15T03:36:42.488320Z","submitted_at":"2024-04-09T02:51:05Z","title":"LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05961","snapshot_observed_at":"2026-08-15T23:29:50.488751Z","title":"LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.488751Z"},"links":{"cited_paper":"/paper/2404.05961","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:6334ed7bdc549267f3b404a09a16d19bca4d8efff3c15a87d593cea9fa61cadc","observation_id":"49bdac78-7b87-4a7e-8a5b-253aa81fc94e","resolution":{"observed_at":"2026-08-15T23:29:50.488751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:29:51.508398Z","title":"SFR-Embedding-Mistral: Enhance Text Retrieval with Transfer Learning,","venue":null,"work_id":"7d97c674-cebd-4e37-a18c-6d35183495f0","year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.493132Z"},"links":{"citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:fd94e0b61b3fed1fea382cc81a36d8ef44f7bc2056f9805eb925bb7435af1e7c","observation_id":"57467ee1-b2a6-45df-bfae-f178e459665f","resolution":{"observed_at":"2026-08-15T23:29:51.513585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17428","last_updated":"2025-02-25T00:35:18Z","snapshot_observed_at":"2026-08-14T08:11:36.232487Z","submitted_at":"2024-05-27T17:59:45Z","title":"NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17428","snapshot_observed_at":"2026-08-15T23:29:50.497194Z","title":"NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.497194Z"},"links":{"cited_paper":"/paper/2405.17428","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:fed98c54c5db7df82441c1e7182f1d61abf09f6e3ee4dde21d613f9e530331f4","observation_id":"cb238a78-7d7e-496c-aeba-ccc7d9966c5a","resolution":{"observed_at":"2026-08-15T23:29:50.497194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.12832","last_updated":"2020-06-04T05:28:21Z","snapshot_observed_at":"2026-08-14T17:33:02.829560Z","submitted_at":"2020-04-27T14:21:03Z","title":"ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.12832","snapshot_observed_at":"2026-08-15T23:29:50.501474Z","title":"ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.501474Z"},"links":{"cited_paper":"/paper/2004.12832","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:003f0c736bf87a1da3a902166c9544adca0d83ea34ca4175056a26b4b191e7cb","observation_id":"78ffa10f-04d3-4016-a52e-4f1aff132c95","resolution":{"observed_at":"2026-08-15T23:29:50.501474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.01488","last_updated":"2022-07-10T17:28:51Z","snapshot_observed_at":"2026-08-13T17:22:55.524190Z","submitted_at":"2021-12-02T18:38:50Z","title":"ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.01488","snapshot_observed_at":"2026-08-15T23:29:50.505844Z","title":"ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.505844Z"},"links":{"cited_paper":"/paper/2112.01488","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:8593e5db569b85a793f2b97af584472c9b8ba5e6c3170726c6e797b734ba3f7d","observation_id":"80595dd4-0892-46a2-84af-4f51ac664b46","resolution":{"observed_at":"2026-08-15T23:29:50.505844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.09675","last_updated":"2020-02-24T18:59:28Z","snapshot_observed_at":"2026-07-29T15:42:51.774083Z","submitted_at":"2019-04-21T23:08:53Z","title":"BERTScore: Evaluating Text Generation with BERT","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09675","snapshot_observed_at":"2026-08-15T23:29:50.510354Z","title":"BERTScore: Evaluating Text Generation with BERT,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.510354Z"},"links":{"cited_paper":"/paper/1904.09675","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:72fe2d686585c30d96702943c87366983400956e584c6a3d844aa334c9c2371e","observation_id":"982e1a9a-5cea-42be-b301-03506f09ef6b","resolution":{"observed_at":"2026-08-15T23:29:50.510354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.01431","last_updated":"2023-12-20T11:54:11Z","snapshot_observed_at":"2026-08-13T10:20:59.304484Z","submitted_at":"2023-09-04T08:28:44Z","title":"Benchmarking Large Language Models in Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.01431","snapshot_observed_at":"2026-08-15T23:29:50.514834Z","title":"Benchmarking Large Language Models in Retrieval-Augmented Generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.514834Z"},"links":{"cited_paper":"/paper/2309.01431","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:922abb0843ed6b36393d9bf692e0094a229eb592ed36b2a34e29ba3e02f40b3b","observation_id":"de9c6e7a-a219-4afe-bc8d-749c8463ebcf","resolution":{"observed_at":"2026-08-15T23:29:50.514834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1611.09268","last_updated":"2018-10-31T14:46:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-11-28T18:14:11Z","title":"MS MARCO: A Human Generated MAchine Reading COmprehension Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.09268","snapshot_observed_at":"2026-08-15T23:29:50.519052Z","title":"MS MARCO: A Human Generated MAchine Reading COmprehension Dataset,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.519052Z"},"links":{"cited_paper":"/paper/1611.09268","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:4c7fb1e5ae73873dc955216afa3e2146bd17d60da1030d9e01ad37cb258f67f5","observation_id":"ba5f30e0-d114-4d6f-a46a-2f61448b3839","resolution":{"observed_at":"2026-08-15T23:29:50.519052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14251","last_updated":"2023-10-11T05:27:50Z","snapshot_observed_at":"2026-08-13T11:35:21.266527Z","submitted_at":"2023-05-23T17:06:00Z","title":"FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14251","snapshot_observed_at":"2026-08-15T23:29:50.523585Z","title":"FActScore: Fine -grained Atomic Evaluation of Factual Precision in Long Form Text Generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T23:29:50.523585Z"},"links":{"cited_paper":"/paper/2305.14251","citing_paper":"/paper/2505.04680"},"observation_digest":"sha256:d4972b76b23a471cbbbf66ff7a143534feec71c9858d7d4ea656fedff921de03","observation_id":"7e09c627-47d9-4ed5-85be-90ed8636de9c","resolution":{"observed_at":"2026-08-15T23:29:50.523585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.04680","last_updated":"2025-05-07T16:12:53Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-16T11:23:32.952305Z","submitted_at":"2025-05-07T16:12:53Z","title":"Retrieval Augmented Generation Evaluation for Health Documents"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":47,"verified_exact":1,"verified_fuzzy":8},"total_outbound_references":57},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2505.04680."}