{"as_of":"2026-08-18T09:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5ab275e484dd22a7ad426b116f2c940199776bf62391cd49a7a6a0497a9d7ab","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T10:29:42.372531Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:48:18.717088Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T05:48:18.949273Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"cited_work":{"arxiv_id":"2411.19203","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.19203","snapshot_observed_at":"2026-08-07T05:48:18.949273Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","venue":"cs.CL","work_id":"cb8f387b-3084-4317-b39e-9888d6f657e8","year":2024},"citing_paper":{"arxiv_id":"2506.11110","last_updated":"2025-06-08T14:08:22Z","snapshot_observed_at":"2026-08-14T14:49:58.241818Z","submitted_at":"2025-06-08T14:08:22Z","title":"AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:48:18.717088Z"},"links":{"cited_paper":"/paper/2411.19203","citing_paper":"/paper/2506.11110"},"observation_digest":"sha256:c11726493555af69906fa08c95439f93c365f407cacd471139ea1df44840ce42","observation_id":"2e5dd03d-1075-4823-9f36-5942d21527f2","resolution":{"observed_at":"2026-08-07T05:48:18.954423Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.19203/citation-record","integrity":"/paper/2411.19203/integrity","json":"/paper/2411.19203/citation-record.json","paper":"/paper/2411.19203"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1409.0473","last_updated":"2016-05-19T21:53:22Z","snapshot_observed_at":"2026-08-18T01:44:19.597420Z","submitted_at":"2014-09-01T16:33:02Z","title":"Neural Machine Translation by Jointly Learning to Align and Translate","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.0473","snapshot_observed_at":"2026-08-12T10:29:42.139145Z","title":"Neural machine translation by jointly learning to align and translate","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.139145Z"},"links":{"cited_paper":"/paper/1409.0473","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:cf3f3cb0dbd028722e912af73dfea79175112d5d24c2084936c64c52d92f02d4","observation_id":"ccb35e09-1de6-4a72-9a38-7570f8b4abc0","resolution":{"observed_at":"2026-08-12T10:29:42.139145Z","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":"10.1609/aaai.v32i1.11944","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.886269Z","title":"Table-to-text: Describing table region with natural language","venue":null,"work_id":"69b1aac5-db39-469a-b470-a3766b521381","year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.145251Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:4a7f879948f61528f943aa438d3f99be39de5ab6933835340a46ee914c34110b","observation_id":"f1154f28-45ce-4897-ae8a-0faec9b228bd","resolution":{"observed_at":"2026-08-12T10:29:42.891140Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.329475Z","title":null,"venue":null,"work_id":"e8af8ecf-82ac-4372-a361-ff0d20536ed6","year":2020},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.150461Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:fb5c080da72a43ea0a11344e8431903e530bcd5abda80b9a32879ebadb77fa35","observation_id":"1f5970e2-bfa5-4b60-97f5-4e4bc92454c7","resolution":{"observed_at":"2026-08-12T10:29:43.333934Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.312117Z","title":"The price of debiasing automatic metrics in natural language evalaution","venue":null,"work_id":"88488288-4ede-44d5-9bee-26923c46e6e1","year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.156233Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:6f3e01fb6e3c1c7ab3d7444b670fe535d7850a9487caae111e80649e6b3c25c0","observation_id":"ab9d3d67-45b3-4ef6-ba32-df7465b69ab5","resolution":{"observed_at":"2026-08-12T10:29:43.318704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.295499Z","title":"Qlora: Efficient finetuning of quantized llms","venue":null,"work_id":"d765af97-eeaf-44c4-accb-4ea59958bc31","year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.161736Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:17a5ac12b6c8540554824a8c60633ebe97b720bdd179e6d4ea982324adbaae25","observation_id":"607635bd-e611-4174-92c1-a76fe76072d0","resolution":{"observed_at":"2026-08-12T10:29:43.300751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.167920Z","title":"Parikh, Ming - Wei Chang, Dipanjan Das, and William W","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.167920Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:89f69cb512c680ad1de0e562bad6b9a2f2c7727e3335ad0139c5cdfec53a13d2","observation_id":"68d581f1-5e2a-4a5f-9ccc-c0b0beb5d580","resolution":{"observed_at":"2026-08-12T10:29:42.167920Z","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":"2026-08-12T10:29:43.278440Z","title":"The hitchhiker's guide to testing statistical significance in natural language processing","venue":null,"work_id":"ab93e4ee-cf3c-4dfc-a043-df4753aa8ab4","year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.173427Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:38a9d96811770e58d102a83f3ac81f91e825ba553da0bdbee75b6a4de4d88da0","observation_id":"9596a39a-921b-46c7-a216-1d39ebcba530","resolution":{"observed_at":"2026-08-12T10:29:43.284598Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.179684Z","title":"Evaluating the state-of-the-art of end-to-end natural language generation: The E2E NLG challenge","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.179684Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:7b9d6e437dc288a003c0b85785fc6da588d5b1dd19bb680138b09f79f6c61486","observation_id":"7d9b1464-ef32-4ace-8dac-a36a1d69bcdd","resolution":{"observed_at":"2026-08-12T10:29:42.179684Z","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":"2026-08-12T10:29:42.185117Z","title":"Fabbri, Chien - Sheng Wu, Wenhao Liu, and Caiming Xiong","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.185117Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:f29e23ef3c293483326172fadb990c2a34bfd7b896a08ace49be10b16ea508ed","observation_id":"ad1b2b6a-b6f4-401b-b2c0-ffe731451b80","resolution":{"observed_at":"2026-08-12T10:29:42.185117Z","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":"2026-08-12T10:29:42.191377Z","title":"The webnlg challenge: Generating text from RDF data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.191377Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:f11648b0b653930601234cefff700d22ab0b761d909284e0e0a635a4bae1e778","observation_id":"413d3889-6536-4d40-8504-abf4f7d0e777","resolution":{"observed_at":"2026-08-12T10:29:42.191377Z","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":"10.1613/jair.5477","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.714816Z","title":"Survey of the state of the art in natural language generation: Core tasks, applications and evaluation","venue":null,"work_id":"2759be61-1d3a-408b-aa73-2cbec21da91d","year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.196507Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:49761291243c5f996d6f0d11cec7fd977272ea0e35ed6fd307fdf4c0034660e0","observation_id":"f5b498ca-7cc1-42ff-850d-1791c3853c72","resolution":{"observed_at":"2026-08-12T10:29:42.719872Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"hash/1190733","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:43.132799Z","title":"Openagi: When LLM meets domain experts","venue":null,"work_id":"4491ef60-08f8-46a1-a29c-439635f83ff5","year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.201838Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:19905cf13f8ecf40dd9b9542117f715600b50e3e24bb555f69849342c633aab4","observation_id":"b613e737-27b2-42d4-b266-392a3dbdbe71","resolution":{"observed_at":"2026-08-12T10:29:43.141796Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.206539Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.206539Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:8e0d26d75de5f273a86c95b0d70db042940ceb277837091ed7720b16cc65e05d","observation_id":"f2233875-fbef-4637-a54b-b65d25e8319b","resolution":{"observed_at":"2026-08-12T10:29:42.206539Z","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":"10.18653/v1/2021.eacl-main.153","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.699185Z","title":"Language models as knowledge bases: On entity representations, storage capacity, and paraphrased queries","venue":null,"work_id":"f96c15a3-1a15-4fff-8e42-f0b0e5c89050","year":2021},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.211252Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:7da07695b9b81fc775216ac52f0436bc6ce90697d848440f840b3826e802e8cd","observation_id":"c2b6ac70-fbec-4f88-8024-68b0dbde5a76","resolution":{"observed_at":"2026-08-12T10:29:42.704270Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.05232","last_updated":"2024-11-19T12:42:45Z","snapshot_observed_at":"2026-07-06T16:45:07.733095Z","submitted_at":"2023-11-09T09:25:37Z","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.05232","snapshot_observed_at":"2026-08-12T10:29:42.216409Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.216409Z"},"links":{"cited_paper":"/paper/2311.05232","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:cd1625d565fecfc00e2ae8b573e2580f698c88f0b9c70776f12681fae45acba0","observation_id":"be8cc0fd-b5fc-4dba-9cd8-6c28f9c793b7","resolution":{"observed_at":"2026-08-12T10:29:42.216409Z","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":"2026-08-12T10:29:42.221775Z","title":"Survey of hallucination in natural language generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.221775Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:e63beb43724a1f091a692dad068442c0ab7a3f7556280353d74cdd8f50737016","observation_id":"3904509d-9ba3-420c-82c5-4aa166c0bf2f","resolution":{"observed_at":"2026-08-12T10:29:42.221775Z","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":"10.18653/v1/n18-1014","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.656076Z","title":null,"venue":null,"work_id":"6d96c8b4-f7f6-4bf2-a2dd-1a85b68da40c","year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.226720Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:13cdee37d6258bfad217e38b9e7726758e2d7e06ec155a0e140bac2f5c8e8cbc","observation_id":"8ef299d7-0742-4898-9ca4-0461b8ef8f56","resolution":{"observed_at":"2026-08-12T10:29:42.661149Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.261333Z","title":null,"venue":null,"work_id":"ca57c88b-197d-4f51-a932-4c5558d31e69","year":2019},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.231814Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:34b1a3072c1854faba7b18fb2aa106a0491609d4a38bf46fe19b7b93556d03d1","observation_id":"fadabe48-820b-47ca-9874-548dfe097b9f","resolution":{"observed_at":"2026-08-12T10:29:43.265998Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10186","last_updated":"2024-06-06T12:29:44Z","snapshot_observed_at":"2026-08-16T14:26:21.863652Z","submitted_at":"2024-01-18T18:15:46Z","title":"Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation","version":3},"cited_work":{"arxiv_id":"2401.10186","doi":"10.48550/arxiv.2401.10186","metadata_source":"pith","pith_arxiv_id":"2401.10186","snapshot_observed_at":"2026-08-12T12:16:16.734455Z","title":"Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation","venue":"cs.CL","work_id":"69fdf942-1dbe-44ce-891b-938f4d78c201","year":2024},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.236606Z"},"links":{"cited_paper":"/paper/2401.10186","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:a18258460f59395e2aa51a79e8f651da9e509aad7dc610e058d010d35533cac9","observation_id":"3ae2ae2e-237a-4794-83b0-33557c68735b","resolution":{"observed_at":"2026-08-12T10:29:42.644920Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.acl-demo.42","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.617231Z","title":"Tabgenie: A toolkit for table-to-text generation","venue":null,"work_id":"5f17c00b-8bd4-4da4-bb57-849d57d685b8","year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.242987Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:af1d1f5b44116a2fcce0c7b091b8b0fcca7e2d4bd9d1516e32ac6571ea765047","observation_id":"912eefeb-4a18-43ab-8f66-0ae9694e0dd1","resolution":{"observed_at":"2026-08-12T10:29:42.622799Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.253038Z","title":"BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.253038Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:140d8de1bebc4858ed3f1918faee62b7987dc3e254829ecafb5631017552570f","observation_id":"e5416308-7e2f-44a5-bb6a-57d7bae3bd8c","resolution":{"observed_at":"2026-08-12T10:29:42.253038Z","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":"10.1162/tacl_a_00641/2346090/tacl_a_00641.pdf","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.578943Z","title":"Unifying structured data as graph for data-to-text pre-training","venue":null,"work_id":"d723cdf6-cf8e-4606-8f2c-64b3c8ba67a2","year":2024},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.257788Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:171aebd1ac8062fdbfb4ebb52003e7624eaccca0e73fd6eb83221e0f26e9c782","observation_id":"e2442c86-6306-403a-a169-6d07a4ed8377","resolution":{"observed_at":"2026-08-12T10:29:42.585275Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.05227","last_updated":"2022-03-10T08:28:32Z","snapshot_observed_at":"2026-08-16T17:15:39.483485Z","submitted_at":"2022-03-10T08:28:32Z","title":"Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.05227","snapshot_observed_at":"2026-08-12T10:29:42.262577Z","title":"Faithfulness in natural language generation: A systematic survey of analysis, evaluation and optimization methods","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.262577Z"},"links":{"cited_paper":"/paper/2203.05227","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:70f9da309974c56c254e0fa4b4072f8d24cd2fc0c1344ee05e3622bd25dc58c4","observation_id":"4a85c06a-aa3f-42da-a778-71060f2001df","resolution":{"observed_at":"2026-08-12T10:29:42.262577Z","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":"2026-08-12T10:29:42.267505Z","title":"A survey on neural data-to-text generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.267505Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:be0fbce64cf01f6a12253455661a7b125ca20953680ca1ddf71dfe6b519f8789","observation_id":"8055ec86-c120-4afa-9555-6b6475a1ed7f","resolution":{"observed_at":"2026-08-12T10:29:42.267505Z","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":"2026-08-12T10:29:43.245875Z","title":"High-quality data-to-text generation for severely under-resourced languages with out-of-the-box large language models","venue":null,"work_id":"566ebeab-75a8-43e9-a468-e66ebf405b90","year":2024},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.272065Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:b0b905d4c737e279c6c165f22c613faaac511be65bfd5d329174d3e068c151d4","observation_id":"0597c271-c7e3-468f-8b14-5721dabdd9ae","resolution":{"observed_at":"2026-08-12T10:29:43.250961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.228967Z","title":"Decoupled weight decay regularization","venue":null,"work_id":"30983379-d43e-43eb-a054-32370c7ee630","year":2019},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.276631Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:d77f9ea474ca0625977870e0a104342177f7824caa96688a1efebf70d4344d9a","observation_id":"06de1b72-3a55-4a64-82ea-fd23a9bc3ac2","resolution":{"observed_at":"2026-08-12T10:29:43.234437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.282779Z","title":"Recurrent neural network based language model","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.282779Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:6c45abb019adb73675582a4ac7e06676c4e414d9d665e5fd626d1fae4da3deca","observation_id":"4258c5b1-4835-4fef-83bc-a8b6f6a33ec2","resolution":{"observed_at":"2026-08-12T10:29:42.282779Z","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":"2026-08-12T10:29:42.288536Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.288536Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:c3344d9703a74fd2cc68ddbd3c6df5059983c9caa68f94bfa4f0ead636771879","observation_id":"271fa63b-48c8-45de-ae6f-96f9e52aaca7","resolution":{"observed_at":"2026-08-12T10:29:42.288536Z","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":"2026-08-12T10:29:43.203049Z","title":"The refinedweb dataset for falcon LLM: outperforming curated corpora with web data only","venue":null,"work_id":"89b9c016-895b-47f7-9942-312053367b4b","year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.293061Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:25605e4e442f01c59d3c280e6c6681101e601ee5fdca73c2aee4b20e5c1b906d","observation_id":"34030352-8d8f-47d5-9b90-1df4466621a4","resolution":{"observed_at":"2026-08-12T10:29:43.207740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.297554Z","title":"Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.297554Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:4abe6310f7d73bedcc385f394545747c5accfa612fd42473c2df4259ac328c4b","observation_id":"12a494f0-8733-4f16-9cb9-b16265f41e8f","resolution":{"observed_at":"2026-08-12T10:29:42.297554Z","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":"2026-08-12T10:29:42.303515Z","title":"Data-to-text generation with macro planning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.303515Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:877fec0ee291efce610bca98a27a9b9411e2849bd16e19dd5493198f3428cf35","observation_id":"850e7c93-d36a-4ca3-877b-89f5d966fcef","resolution":{"observed_at":"2026-08-12T10:29:42.303515Z","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":"2026-08-12T10:29:43.186851Z","title":null,"venue":null,"work_id":"996b712b-a66d-41cc-b1e5-9f5602bbef92","year":2020},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.308188Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:e721a359500017e0e56841e5f936dee32dd61258d70766a36552bed234574f82","observation_id":"676638fe-08bd-4b39-9cb3-eb6e2f4d9116","resolution":{"observed_at":"2026-08-12T10:29:43.191539Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.313465Z","title":"A structured review of the validity of BLEU","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.313465Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:001853510d057941d9586dab3d8f17ed2edd812efe7e58e13ba6e962c17e4fc7","observation_id":"9d9d6b6f-bf1f-42d8-8a10-7b0cd540d3ab","resolution":{"observed_at":"2026-08-12T10:29:42.313465Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.05100","last_updated":"2023-06-27T09:57:58Z","snapshot_observed_at":"2026-08-04T18:56:03.233715Z","submitted_at":"2022-11-09T18:48:09Z","title":"BLOOM: A 176B-Parameter Open-Access Multilingual Language Model","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.05100","snapshot_observed_at":"2026-08-12T10:29:42.318237Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.318237Z"},"links":{"cited_paper":"/paper/2211.05100","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:630875ac0e8e8ee4efb05f8e9f9ef1b5445cc2b92d9c91f955b5b3b66cc9e34b","observation_id":"f14009bc-7993-4fcc-bd87-8842dcdb56fc","resolution":{"observed_at":"2026-08-12T10:29:42.318237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.08684","last_updated":"2020-11-02T13:25:33Z","snapshot_observed_at":"2026-07-06T08:30:40.946002Z","submitted_at":"2019-10-19T03:00:46Z","title":"Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.08684","snapshot_observed_at":"2026-08-12T10:29:42.323709Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.323709Z"},"links":{"cited_paper":"/paper/1910.08684","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:78d0dd20454fa9686398db7de5a0c295afd4f5b9398534c3388426af8db2b6ea","observation_id":"58994a10-0d49-494c-9d1a-31943c4736e8","resolution":{"observed_at":"2026-08-12T10:29:42.323709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-12T10:29:42.329926Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.329926Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:b7a128d8d425e0a1b83b735e3fc462299656703e3b5e64ea93876a5b034b3ade","observation_id":"3706d22a-7b56-4630-8c18-3a6ad2dca0a7","resolution":{"observed_at":"2026-08-12T10:29:42.329926Z","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":"10.18653/v1/2023.inlg-main.30","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.482149Z","title":"Tackling hallucinations in neural chart summarization","venue":null,"work_id":"b954ade4-56ca-495d-9408-4b503065d631","year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.335056Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:81237a6925d21bf041f7b8d4d6eede95d8b3c755d3b6657c12aad052a23ef677","observation_id":"ed061eff-25f3-4b41-ba29-aacad5dca9e5","resolution":{"observed_at":"2026-08-12T10:29:42.489700Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T10:29:43.170701Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":"bf4805da-7964-47ca-ba2f-b2998f093f1e","year":2017},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.339812Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:2f432197a4641570455900e849032662efbc3fb1a94e76b6cbc386fa95647ef1","observation_id":"88d65bc4-9696-4e80-a8aa-91dcb5a83f8c","resolution":{"observed_at":"2026-08-12T10:29:43.175391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:29:42.344587Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.344587Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:42d5dd1efbbd1ab9dcb99951bbb7775f36c08ae960aac6307112a80ca81e9228","observation_id":"6f34108d-7b5a-4d5a-b3e6-a5bb7fbd1f1a","resolution":{"observed_at":"2026-08-12T10:29:42.344587Z","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":"2026-08-12T10:29:42.349704Z","title":"On hallucination and predictive uncertainty in conditional language generation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.349704Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:4fba20aaaa6a311288259f5faf5d472bfd3193184df1e8de032b7a03a0be0eb5","observation_id":"f21186db-fdcb-4198-b8d3-faab266ef7b5","resolution":{"observed_at":"2026-08-12T10:29:42.349704Z","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":"2026-08-12T10:29:42.355374Z","title":"Biomedical data-to-text generation via fine-tuning transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.355374Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:065ef252c61e4508cfc00817f2a7aad8eeb356077f0e198c1a901b03f1d68b1a","observation_id":"f9887531-75a3-42a6-a598-e1a9c3d7f8b8","resolution":{"observed_at":"2026-08-12T10:29:42.355374Z","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":"2026-08-12T10:29:42.361037Z","title":"Alignscore: Evaluating factual consistency with A unified alignment function","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.361037Z"},"links":{"citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:275cd283fde63c3078a208fe52f8834fdb8e2681505fd7a23ac2f70a7e0a3d10","observation_id":"9f3997e4-7bac-4d0d-a241-394abd32553c","resolution":{"observed_at":"2026-08-12T10:29:42.361037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01068","last_updated":"2022-06-21T17:04:40Z","snapshot_observed_at":"2026-08-06T03:13:37.403059Z","submitted_at":"2022-05-02T17:49:50Z","title":"OPT: Open Pre-trained Transformer Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01068","snapshot_observed_at":"2026-08-12T10:29:42.366200Z","title":"Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.366200Z"},"links":{"cited_paper":"/paper/2205.01068","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:e514c949663fe44d2062dba5db5bd190ebd9d8c6bad13396bba67938082bcbb2","observation_id":"3746d1d0-f3fe-4cdb-b8be-125126e316c8","resolution":{"observed_at":"2026-08-12T10:29:42.366200Z","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":"2026-08-16T12:38:46.158503Z","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":"2026-08-12T10:29:42.372531Z","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":"2411.19203","last_updated":"2024-11-28T15:23:12Z","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-12T10:29:42.372531Z"},"links":{"cited_paper":"/paper/2309.01219","citing_paper":"/paper/2411.19203"},"observation_digest":"sha256:bea48e20716c63845f555f1e97ef264b0fd7285e1ec1ec6beea700c502e4f5c7","observation_id":"fd845d49-9655-431a-ad04-5776a5662f27","resolution":{"observed_at":"2026-08-12T10:29:42.372531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.19203","last_updated":"2024-11-28T15:23:12Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T14:14:27.770693Z","submitted_at":"2024-11-28T15:23:12Z","title":"An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":26,"verified_exact":9,"verified_fuzzy":7},"total_outbound_references":44},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2411.19203."}