mlsanityData to 7 Oct 2026

Read before Generate! Faithful Long Form Question Answering with Machine Reading

arXiv 2203.00343 ↗First posted 1 Mar 2022cs.CL cs.AIcited by 47

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Abstract (arXiv)

Long-form question answering (LFQA) aims to generate a paragraph-length answer for a given question. While current work on LFQA using large pre-trained model for generation are effective at producing fluent and somewhat relevant content, one primary challenge lies in how to generate a faithful answer that has less hallucinated content. We propose a new end-to-end framework that jointly models answer generation and machine reading. The key idea is to augment the generation model with fine-grained, answer-related salient information which can be viewed as an emphasis on faithful facts. State-of-the-art results on two LFQA datasets, ELI5 and MS MARCO, demonstrate the effectiveness of our method, in comparison with strong baselines on automatic and human evaluation metrics. A detailed analysis further proves the competency of our methods in generating fluent, relevant, and more faithful answers.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Builds on 36 of its 66 references that are in the map. First posted on arXiv 1 Mar 2022.

Builds on

36 of 66 references.

References · 36

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  5. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  6. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  7. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  8. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,895
  9. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  10. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  11. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  12. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
24 more
  1. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  2. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  3. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  4. 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 713
  5. 2019Latent Retrieval for Weakly Supervised Open Domain Question Answeringcited by 691
  6. 2020KILT: a Benchmark for Knowledge Intensive Language Taskscited by 571
  7. 2019ELI5: Long Form Question Answeringcited by 567
  8. 2018Wizard of Wikipedia: Knowledge-Powered Conversational agentscited by 530
  9. 2017Zero-Shot Relation Extraction via Reading Comprehensioncited by 425
  10. 2020Asking and Answering Questions to Evaluate the Factual Consistency of Summariescited by 376
  11. 2016NewsQA: A Machine Comprehension Datasetcited by 330
  12. 2020FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarizationcited by 292
  13. 2017SearchQA: A New Q&A Dataset Augmented with Context from a Search Enginecited by 221
  14. 2019MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehensioncited by 183
  15. 2020How Context Affects Language Models' Factual Predictionscited by 181
  16. 2021Hurdles to Progress in Long-form Question Answeringcited by 166
  17. 2018A Dataset for Document Grounded Conversationscited by 104
  18. 2021GooAQ: Open Question Answering with Diverse Answer Typescited by 53
  19. 2020A Controllable Model of Grounded Response Generationcited by 49
  20. 2018Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Modelscited by 39
  21. 2020Multi-hop Question Generation with Graph Convolutional Networkcited by 20
  22. 2017Augmenting End-to-End Dialog Systems with Commonsense Knowledgecited by 18
  23. 2021Improve Query Focused Abstractive Summarization by Incorporating Answer Relevancecited by 15
  24. 2020Studying Strategically: Learning to Mask for Closed-book QAcited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 5; 2023: 15; 2024: 21; 2025: 5; 2026: 1.

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  1. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  2. 2024Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMscited by 246
  3. 2022Factuality Enhanced Language Models for Open-Ended Text Generationcited by 200
  4. 2023Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigationcited by 123
  5. 2023A Critical Evaluation of Evaluations for Long-form Question Answeringcited by 111
  6. 2023Enhancing Uncertainty-Based Hallucination Detection with Stronger Focuscited by 98
  7. 2023Towards Mitigating Hallucination in Large Language Models via Self-Reflectioncited by 81
  8. 2022Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-trainingcited by 71
  9. 2024SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMscited by 67
  10. 2023PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documentscited by 61
  11. 2023Why Does ChatGPT Fall Short in Providing Truthful Answers?cited by 54
  12. 2023DelucionQA: Detecting Hallucinations in Domain-specific Question Answeringcited by 43
35 more
  1. 2023"According to ...": Prompting Language Models Improves Quoting from Pre-Training Datacited by 42
  2. 2023Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answeringcited by 41
  3. 2024Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Modelscited by 24
  4. 2024Estimating the Hallucination Rate of Generative AIcited by 20
  5. 2022How Do We Answer Complex Questions: Discourse Structure of Long-form Answerscited by 19
  6. 2024Know When To Stop: A Study of Semantic Drift in Text Generationcited by 18
  7. 2025OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinkingcited by 18
  8. 2024KnowTuning: Knowledge-aware Fine-tuning for Large Language Modelscited by 11
  9. 2023Optimizing Retrieval-augmented Reader Models via Token Eliminationcited by 10
  10. 2022Context Generation Improves Open Domain Question Answeringcited by 7
  11. 2024Groundedness in Retrieval-augmented Long-form Generation: An Empirical Studycited by 7
  12. 2024Integrating Planning into Single-Turn Long-Form Text Generationcited by 7
  13. 2024Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Surveycited by 6
  14. 2024SELU: Self-Learning Embodied MLLMs in Unknown Environmentscited by 6
  15. 2023Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approachcited by 4
  16. 2024Localizing and Mitigating Errors in Long-form Question Answeringcited by 4
  17. 2024A Benchmark Dataset with Larger Context for Non-Factoid Question Answering over Islamic Textcited by 4
  18. 2024Learning from Many Voices: Literary MT Using Multi-Reference Human and Synthetic Datacited by 3
  19. 2025Extract, Match, and Score: An Evaluation Paradigm for Long Question-context-answer Triplets in Financial Analysiscited by 3
  20. 2022A Pipeline for Generating, Annotating and Employing Synthetic Data for Real World Question Answeringcited by 2
  21. 2023Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answeringcited by 2
  22. 2024Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspectivecited by 2
  23. 2023Improving Query-Focused Meeting Summarization with Query-Relevant Knowledgecited by 1
  24. 2023Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learningcited by 1
  25. 2024Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfercited by 1
  26. 2024Multi-Review Fusion-in-Contextcited by 1
  27. 2024LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarizationcited by 1
  28. 2024Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answeringcited by 1
  29. 2025EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answeringcited by 1
  30. 2025Towards Mitigation of Hallucination for LLM-empowered Agents: Progressive Generalization Bound Exploration and Watchdog Monitorcited by 1
  31. 2024QASE Enhanced PLMs: Improved Control in Text Generation for MRCcited by 0
  32. 2024Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehensioncited by 0
  33. 2024Retrieving Contextual Information for Long-Form Question Answering using Weak Supervisioncited by 0
  34. 2025Invoke Interfaces Only When Needed: Adaptive Invocation for Large Language Models in Question Answeringcited by 0
  35. 2026LFQA-HP-1M: A Large-Scale Human Preference Dataset for Long-Form Question Answeringcited by 0