mlsanityData to 14 Oct 2026

Conformal Language Modeling

arXiv 2306.10193 ↗First posted 16 Jun 2023cs.CL cs.LGcited by 170

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Cited by 23 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We propose a novel approach to conformal prediction for generative language models (LMs). Standard conformal prediction produces prediction sets -- in place of single predictions -- that have rigorous, statistical performance guarantees. LM responses are typically sampled from the model's predicted distribution over the large, combinatorial output space of natural language. Translating this process to conformal prediction, we calibrate a stopping rule for sampling different outputs from the LM that get added to a growing set of candidates until we are confident that the output set is sufficient. Since some samples may be low-quality, we also simultaneously calibrate and apply a rejection rule for removing candidates from the output set to reduce noise. Similar to conformal prediction, we prove that the sampled set returned by our procedure contains at least one acceptable answer with high probability, while still being empirically precise (i.e., small) on average. Furthermore, within this set of candidate responses, we show that we can also accurately identify subsets of individual components -- such as phrases or sentences -- that are each independently correct (e.g., that are not "hallucinations"), again with statistical guarantees. We demonstrate the promise of our approach on multiple tasks in open-domain question answering, text summarization, and radiology report generation using different LM variants.

Key facts. Cited by 170 papers in the map (data through 14 Oct 2026). Builds on 65 of its 85 references that are in the map. First posted on arXiv 16 Jun 2023.

Builds on

65 of 85 references.

References · 65

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  6. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
  7. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
  8. 2019The Curious Case of Neural Text Degenerationcited by 2,916
  9. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,682
  10. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
  11. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
  12. 2022Language Models (Mostly) Know What They Knowcited by 1,856
38 more
  1. 2015A large annotated corpus for learning natural language inferencecited by 1,847
  2. 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,475
  3. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  4. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,292
  5. 2020RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Modelscited by 1,255
  6. 2015Teaching Machines to Read and Comprehendcited by 1,049
  7. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 905
  8. 2023Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generationcited by 819
  9. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  10. 2022Teaching Models to Express Their Uncertainty in Wordscited by 751
  11. 2016Distribution-Free Predictive Inference For Regressioncited by 668
  12. 2019Conformalized Quantile Regressioncited by 629
  13. 2019MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographscited by 597
  14. 2020How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answeringcited by 445
  15. 2021SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarizationcited by 407
  16. 2019PAWS: Paraphrase Adversaries from Word Scramblingcited by 402
  17. 2020Uncertainty Sets for Image Classifiers using Conformal Predictioncited by 366
  18. 2020CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERTcited by 337
  19. 2020Calibration of Pre-trained Transformerscited by 315
  20. 2022Confident Adaptive Language Modelingcited by 310
  21. 2023Evaluating Verifiability in Generative Search Enginescited by 303
  22. 2022Conformal Risk Controlcited by 299
  23. 2021Distribution-Free, Risk-Controlling Prediction Setscited by 288
  24. 2021Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcited by 271
  25. 2021QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarizationcited by 236
  26. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 225
  27. 2019Predictive inference with the jackknife+cited by 211
  28. 2020Reducing conversational agents' overconfidence through linguistic calibrationcited by 210
  29. 2021Challenges in Detoxifying Language Modelscited by 169
  30. 2021Hurdles to Progress in Long-form Question Answeringcited by 167
  31. 2020Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generationcited by 141
  32. 2019Clinically Accurate Chest X-Ray Report Generationcited by 139
  33. 2022Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Modelscited by 112
  34. 2022Capturing Failures of Large Language Models via Human Cognitive Biasescited by 98
  35. 2022Improving Chest X-Ray Report Generation by Leveraging Warm Startingcited by 95
  36. 2020Distribution-free binary classification: prediction sets, confidence intervals and calibrationcited by 79
  37. 2021Consistent Accelerated Inference via Confident Adaptive Transformerscited by 74
  38. 2023Automatic Evaluation of Attribution by Large Language Modelscited by 72

50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 6; 2024: 44; 2025: 42; 2026: 78.

170 papers.

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  1. 2023Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignmentcited by 401
  2. 2023Robots That Ask For Help: Uncertainty Alignment for Large Language Model Plannerscited by 308
  3. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)cited by 172
  4. 2024Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similaritiescited by 159
  5. 2024Language Models with Conformal Factuality Guaranteescited by 131
  6. 2024Benchmarking LLMs via Uncertainty Quantificationcited by 126
  7. 2024A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directionscited by 121
  8. 2025Uncertainty Quantification and Confidence Calibration in Large Language Models: A Surveycited by 95
  9. 2024Large language model validity via enhanced conformal prediction methodscited by 92
  10. 2024Towards Conversational Diagnostic AIcited by 79
  11. 2024Mitigating LLM Hallucinations via Conformal Abstentioncited by 59
  12. 2024Conformal Alignment: Knowing When to Trust Foundation Models with Guaranteescited by 54
38 more
  1. 2023Conformal Prediction for Deep Classifier via Label Rankingcited by 53
  2. 2024Conformal Prediction for Natural Language Processing: A Surveycited by 53
  3. 2024Multicalibration for Confidence Scoring in LLMscited by 46
  4. 2024Improving Uncertainty Estimation through Semantically Diverse Language Generationcited by 35
  5. 2024Fast yet Safe: Early-Exiting with Risk Controlcited by 30
  6. 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Surveycited by 30
  7. 2024Uncertainty-Aware Evaluation for Vision-Language Modelscited by 29
  8. 2024Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networkscited by 28
  9. 2024C-RAG: Certified Generation Risks for Retrieval-Augmented Language Modelscited by 27
  10. 2025Analyzing Uncertainty of LLM-as-a-Judge: Interval Evaluations with Conformal Predictioncited by 27
  11. 2024Conformal Prediction: A Data Perspectivecited by 25
  12. 2026Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judgescited by 24
  13. 2025Multivariate Conformal Prediction using Optimal Transportcited by 22
  14. 2023Forking Uncertainties: Reliable Prediction and Model Predictive Control with Sequence Models via Conformal Risk Controlcited by 20
  15. 2024Trustworthy Classification through Rank-Based Conformal Prediction Setscited by 20
  16. 2025Conformal Linguistic Calibration: Trading-off between Factuality and Specificitycited by 20
  17. 2025CP-Router: An Uncertainty-Aware Router Between LLM and LRMcited by 20
  18. 2026Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunitiescited by 20
  19. 2024Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Modelscited by 19
  20. 2024Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measurecited by 18
  21. 2024Prune 'n Predict: Optimizing LLM Decision-making with Conformal Predictioncited by 18
  22. 2023Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Modelscited by 17
  23. 2024Hallucination Detection in Foundation Models for Decision-Making: A Flexible Definition and Review of the State of the Artcited by 17
  24. 2025E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testingcited by 17
  25. 2023Conformal Autoregressive Generation: Beam Search with Coverage Guaranteescited by 16
  26. 2024Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planningcited by 16
  27. 2024On Subjective Uncertainty Quantification and Calibration in Natural Language Generationcited by 16
  28. 2024Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selectioncited by 15
  29. 2024Active, anytime-valid risk controlling prediction setscited by 14
  30. 2025Don't lie to your friends: Learning what you know from collaborative self-playcited by 14
  31. 2025Conformal Language Model Reasoning with Coherent Factualitycited by 14
  32. 2025Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Modelscited by 12
  33. 2024PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attackscited by 11
  34. 2024Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filteringcited by 10
  35. 2024Conformal Structured Predictioncited by 10
  36. 2024TorchCP: A Python Library for Conformal Predictioncited by 9
  37. 2025C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Modelscited by 9
  38. 2024Building a stable classifier with the inflated argmaxcited by 8

50 most cited of 170 All 170 (JSON)