Paper Citation Record · LEDGER

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation

As of 21 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2411.19203.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.19203 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:29:42.372531Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:48:18.717088Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T05:48:18.949273Z

Reference resolution

44 of 44 outbound references displayed

verified exact9
verified fuzzy7
unresolved26
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ccb35e09-1de6-4a72-9a38-7570f8b4abc0 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Neural Machine Translation by Jointly Learning to Align and Translate

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.139145Z

Source-reported events for the cited work

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Observation f1154f28-45ce-4897-ae8a-0faec9b228bd · outbound

This paper cites Table-to-text: Describing table region with natural language.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Table-to-text: Describing table region with natural language

Reference 2

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.891140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1f5970e2-bfa5-4b60-97f5-4e4bc92454c7 · outbound

This paper cites an unresolved cited work.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:29:43.333934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab9d3d67-45b3-4ef6-ba32-df7465b69ab5 · outbound

This paper cites The price of debiasing automatic metrics in natural language evalaution.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation The price of debiasing automatic metrics in natural language evalaution

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.318704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 607635bd-e611-4174-92c1-a76fe76072d0 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Qlora: Efficient finetuning of quantized llms

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.300751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 68d581f1-5e2a-4a5f-9ccc-c0b0beb5d580 · outbound

This paper cites Parikh, Ming - Wei Chang, Dipanjan Das, and William W.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Parikh, Ming - Wei Chang, Dipanjan Das, and William W

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.167920Z

Source-reported events for the cited work

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Observation 9596a39a-921b-46c7-a216-1d39ebcba530 · outbound

This paper cites The hitchhiker's guide to testing statistical significance in natural language processing.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation The hitchhiker's guide to testing statistical significance in natural language processing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.284598Z

Source-reported events for the cited work

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Observation 7d9b1464-ef32-4ace-8dac-a36a1d69bcdd · outbound

This paper cites Evaluating the state-of-the-art of end-to-end natural language generation: The E2E NLG challenge.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Evaluating the state-of-the-art of end-to-end natural language generation: The E2E NLG challenge

Reference 8

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Source-reported events for the cited work

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Observation ad1b2b6a-b6f4-401b-b2c0-ffe731451b80 · outbound

This paper cites Fabbri, Chien - Sheng Wu, Wenhao Liu, and Caiming Xiong.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Fabbri, Chien - Sheng Wu, Wenhao Liu, and Caiming Xiong

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.185117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 413d3889-6536-4d40-8504-abf4f7d0e777 · outbound

This paper cites The webnlg challenge: Generating text from RDF data.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation The webnlg challenge: Generating text from RDF data

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.191377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5b498ca-7cc1-42ff-850d-1791c3853c72 · outbound

This paper cites Survey of the state of the art in natural language generation: Core tasks, applications and evaluation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Survey of the state of the art in natural language generation: Core tasks, applications and evaluation

Reference 11

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.719872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b613e737-27b2-42d4-b266-392a3dbdbe71 · outbound

This paper cites Openagi: When LLM meets domain experts.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Openagi: When LLM meets domain experts

Reference 12

Resolution: verified exact; raw_fallback, observed 2026-08-12T10:29:43.141796Z

Source-reported events for the cited work

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Observation f2233875-fbef-4637-a54b-b65d25e8319b · outbound

This paper cites an unresolved cited work.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 13

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Source-reported events for the cited work

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Observation c2b6ac70-fbec-4f88-8024-68b0dbde5a76 · outbound

This paper cites Language models as knowledge bases: On entity representations, storage capacity, and paraphrased queries.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Language models as knowledge bases: On entity representations, storage capacity, and paraphrased queries

Reference 14

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.704270Z

Source-reported events for the cited work

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Observation be8cc0fd-b5fc-4dba-9cd8-6c28f9c793b7 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 15

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Source-reported events for the cited work

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Observation 3904509d-9ba3-420c-82c5-4aa166c0bf2f · outbound

This paper cites Survey of hallucination in natural language generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Survey of hallucination in natural language generation

Reference 16

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Source-reported events for the cited work

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Observation 8ef299d7-0742-4898-9ca4-0461b8ef8f56 · outbound

This paper cites an unresolved cited work.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 17

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.661149Z

Source-reported events for the cited work

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Observation fadabe48-820b-47ca-9874-548dfe097b9f · outbound

This paper cites an unresolved cited work.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:29:43.265998Z

Source-reported events for the cited work

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Observation 3ae2ae2e-237a-4794-83b0-33557c68735b · outbound

This paper cites Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-12T10:29:42.644920Z

Source-reported events for the cited work

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Observation 912eefeb-4a18-43ab-8f66-0ae9694e0dd1 · outbound

This paper cites Tabgenie: A toolkit for table-to-text generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Tabgenie: A toolkit for table-to-text generation

Reference 20

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.622799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5416308-7e2f-44a5-bb6a-57d7bae3bd8c · outbound

This paper cites BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.253038Z

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Observation e2442c86-6306-403a-a169-6d07a4ed8377 · outbound

This paper cites Unifying structured data as graph for data-to-text pre-training.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unifying structured data as graph for data-to-text pre-training

Reference 23

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.585275Z

Source-reported events for the cited work

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Observation 4a85c06a-aa3f-42da-a778-71060f2001df · outbound

This paper cites Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods

Reference 24

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Observation 8055ec86-c120-4afa-9555-6b6475a1ed7f · outbound

This paper cites A survey on neural data-to-text generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation A survey on neural data-to-text generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.267505Z

Source-reported events for the cited work

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Observation 0597c271-c7e3-468f-8b14-5721dabdd9ae · outbound

This paper cites High-quality data-to-text generation for severely under-resourced languages with out-of-the-box large language models.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation High-quality data-to-text generation for severely under-resourced languages with out-of-the-box large language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.250961Z

Source-reported events for the cited work

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Observation 06de1b72-3a55-4a64-82ea-fd23a9bc3ac2 · outbound

This paper cites Decoupled weight decay regularization.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Decoupled weight decay regularization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.234437Z

Source-reported events for the cited work

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Observation 4258c5b1-4835-4fef-83bc-a8b6f6a33ec2 · outbound

This paper cites Recurrent neural network based language model.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Recurrent neural network based language model

Reference 28

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Observation 271fa63b-48c8-45de-ae6f-96f9e52aaca7 · outbound

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An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 29

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Source-reported events for the cited work

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Observation 34030352-8d8f-47d5-9b90-1df4466621a4 · outbound

This paper cites The refinedweb dataset for falcon LLM: outperforming curated corpora with web data only.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation The refinedweb dataset for falcon LLM: outperforming curated corpora with web data only

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.207740Z

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Observation 12a494f0-8733-4f16-9cb9-b16265f41e8f · outbound

This paper cites Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer

Reference 31

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Observation 850e7c93-d36a-4ca3-877b-89f5d966fcef · outbound

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An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Data-to-text generation with macro planning

Reference 32

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Observation 676638fe-08bd-4b39-9cb3-eb6e2f4d9116 · outbound

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An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation 9d9d6b6f-bf1f-42d8-8a10-7b0cd540d3ab · outbound

This paper cites A structured review of the validity of BLEU.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation A structured review of the validity of BLEU

Reference 34

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Observation f14009bc-7993-4fcc-bd87-8842dcdb56fc · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 35

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Observation 58994a10-0d49-494c-9d1a-31943c4736e8 · outbound

This paper cites Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation

Reference 36

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Observation 3706d22a-7b56-4630-8c18-3a6ad2dca0a7 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 37

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Observation ed061eff-25f3-4b41-ba29-aacad5dca9e5 · outbound

This paper cites Tackling hallucinations in neural chart summarization.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Tackling hallucinations in neural chart summarization

Reference 38

Resolution: verified exact; doi, observed 2026-08-12T10:29:42.489700Z

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Observation 88d65bc4-9696-4e80-a8aa-91dcb5a83f8c · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:29:43.175391Z

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Observation 6f34108d-7b5a-4d5a-b3e6-a5bb7fbd1f1a · outbound

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An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Unresolved cited work

Reference 40

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Observation f21186db-fdcb-4198-b8d3-faab266ef7b5 · outbound

This paper cites On hallucination and predictive uncertainty in conditional language generation.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation On hallucination and predictive uncertainty in conditional language generation

Reference 41

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Observation f9887531-75a3-42a6-a598-e1a9c3d7f8b8 · outbound

This paper cites Biomedical data-to-text generation via fine-tuning transformers.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Biomedical data-to-text generation via fine-tuning transformers

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.355374Z

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Observation 9f3997e4-7bac-4d0d-a241-394abd32553c · outbound

This paper cites Alignscore: Evaluating factual consistency with A unified alignment function.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Alignscore: Evaluating factual consistency with A unified alignment function

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.361037Z

Source-reported events for the cited work

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Observation 3746d1d0-f3fe-4cdb-b8be-125126e316c8 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation OPT: Open Pre-trained Transformer Language Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.366200Z

Source-reported events for the cited work

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Observation fd845d49-9655-431a-ad04-5776a5662f27 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T10:29:42.372531Z

Source-reported events for the cited work

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Pith citing papers

Observation 2e5dd03d-1075-4823-9f36-5942d21527f2 · inbound

AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models cites this paper.

AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:48:18.954423Z

Source-reported events for the cited work

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