mlsanityData to 7 Oct 2026

API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access

arXiv 2403.01216 ↗First posted 2 Mar 2024cs.CL cs.AI cs.LGcited by 68

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Abstract (arXiv)

This study aims to address the pervasive challenge of quantifying uncertainty in large language models (LLMs) without logit-access. Conformal Prediction (CP), known for its model-agnostic and distribution-free features, is a desired approach for various LLMs and data distributions. However, existing CP methods for LLMs typically assume access to the logits, which are unavailable for some API-only LLMs. In addition, logits are known to be miscalibrated, potentially leading to degraded CP performance. To tackle these challenges, we introduce a novel CP method that (1) is tailored for API-only LLMs without logit-access; (2) minimizes the size of prediction sets; and (3) ensures a statistical guarantee of the user-defined coverage. The core idea of this approach is to formulate nonconformity measures using both coarse-grained (i.e., sample frequency) and fine-grained uncertainty notions (e.g., semantic similarity). Experimental results on both close-ended and open-ended Question Answering tasks show our approach can mostly outperform the logit-based CP baselines.

Key facts. Cited by 68 papers in the map (data through 7 Oct 2026). Builds on 27 of its 48 references that are in the map. First posted on arXiv 2 Mar 2024.

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27 of 48 references.

References · 27

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  3. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  5. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,416
  6. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,888
  7. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,895
  8. 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,471
  9. 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
  10. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,116
  11. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 777
  12. 2022Teaching Models to Express Their Uncertainty in Wordscited by 731
15 more
  1. 2023Larger language models do in-context learning differentlycited by 386
  2. 2020Uncertainty Sets for Image Classifiers using Conformal Predictioncited by 365
  3. 2020Calibration of Pre-trained Transformerscited by 307
  4. 2016Least Ambiguous Set-Valued Classifiers with Bounded Error Levelscited by 270
  5. 2021Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcited by 256
  6. 2018Learning Confidence for Out-of-Distribution Detection in Neural Networkscited by 245
  7. 2023Conformal Prediction with Large Language Models for Multi-Choice Question Answeringcited by 131
  8. 2015Posterior calibration and exploratory analysis for natural language processing modelscited by 75
  9. 2023Conformal Prediction for Deep Classifier via Label Rankingcited by 52
  10. 2021Prevent the Language Model from being Overconfident in Neural Machine Translationcited by 34
  11. 2022Detection of Word Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimationcited by 32
  12. 2022Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcitycited by 24
  13. 2021Conformal prediction for text infilling and part-of-speech predictioncited by 22
  14. 2023Equal Opportunity of Coverage in Fair Regressioncited by 16
  15. 2023Evaluation of medium-large Language Models at zero-shot closed book generative question answeringcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 13; 2025: 26; 2026: 29.

68 papers.

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  1. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)cited by 170
  2. 2024A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directionscited by 115
  3. 2025Uncertainty Quantification and Confidence Calibration in Large Language Models: A Surveycited by 93
  4. 2024ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guaranteescited by 62
  5. 2024Conformal Alignment: Knowing When to Trust Foundation Models with Guaranteescited by 50
  6. 2024Knowledge Boundary of Large Language Models: A Surveycited by 36
  7. 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Surveycited by 29
  8. 2025Analyzing Uncertainty of LLM-as-a-Judge: Interval Evaluations with Conformal Predictioncited by 26
  9. 2024Conformal Prediction: A Data Perspectivecited by 25
  10. 2025Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topologycited by 24
  11. 2025CP-Router: An Uncertainty-Aware Router Between LLM and LRMcited by 19
  12. 2024Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Modelscited by 18
38 more
  1. 2024EfficientEQA: An Efficient Approach to Open-Vocabulary Embodied Question Answeringcited by 15
  2. 2024Prune 'n Predict: Optimizing LLM Decision-making with Conformal Predictioncited by 15
  3. 2026When and What to Ask: AskBench and Rubric-Guided RLVR for LLM Clarificationcited by 12
  4. 2025Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regressioncited by 10
  5. 2025Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Modelscited by 10
  6. 2025ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guaranteescited by 9
  7. 2025AmbiK: Dataset of Ambiguous Tasks in Kitchen Environmentcited by 8
  8. 2026The Fragility Of Moral Judgment In Large Language Modelscited by 8
  9. 2024C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction Setscited by 7
  10. 2025Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Modelscited by 7
  11. 2025Conformal Information Pursuit for Interactively Guiding Large Language Modelscited by 7
  12. 2026VLM Judges Can Rank but Cannot Score: Task-Dependent Uncertainty in Multimodal Evaluationcited by 7
  13. 2025Domain-Shift-Aware Conformal Prediction for Large Language Modelscited by 6
  14. 2025Human-AI Collaborative Uncertainty Quantificationcited by 6
  15. 2026From Debate to Decision: Conformal Social Choice for Safe Multi-Agent Deliberationcited by 6
  16. 2024Spatial-Aware Conformal Prediction for Trustworthy Hyperspectral Image Classificationcited by 5
  17. 2025COPU: Conformal Prediction for Uncertainty Quantification in Natural Language Generationcited by 5
  18. 2025Adaptive Coverage Policies in Conformal Predictioncited by 4
  19. 2025CritiCal: Can Critique Help LLM Uncertainty or Confidence Calibration?cited by 4
  20. 2026Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignmentcited by 4
  21. 2024Calibrated Large Language Models for Binary Question Answeringcited by 3
  22. 2025Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Reviewcited by 3
  23. 2025Quantifying Uncertainty in Natural Language Explanations of Large Language Models for Question Answeringcited by 3
  24. 2026Remember with Confidence: Uncertainty Quantification for Spatio-temporal Memory with Probabilistic Guaranteescited by 3
  25. 2025Filtering with Confidence: When Data Augmentation Meets Conformal Predictioncited by 2
  26. 2025Robust Uncertainty Quantification for Self-Evolving Large Language Models via Continual Domain Pretrainingcited by 2
  27. 2026Large-Language-Model-Guided State Estimation for Partially Observable Task and Motion Planningcited by 2
  28. 2026Credal Large Language Models for Semantic Commitment under Uncertaintycited by 2
  29. 2024Threshold Filtering Packing for Supervised Fine-Tuning: Training Related Samples within Packscited by 1
  30. 2025Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Scorecited by 1
  31. 2025Uncertainty-aware Reward Design Processcited by 1
  32. 2025SpeedCP: Fast Kernel-based Conditional Conformal Predictioncited by 1
  33. 2025Provably Minimum-Length Conformal Prediction Sets for Ordinal Classificationcited by 1
  34. 2026CAOS: Conformal Aggregation of One-Shot Predictorscited by 1
  35. 2026From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Modelscited by 1
  36. 2026Bayesian Elicitation with LLMs: Model Size Helps, Extra "Reasoning" Doesn't Alwayscited by 1
  37. 2026Beyond Surface Statistics: Robust Conformal Prediction for LLMs via Internal Representationscited by 1
  38. 2026Differentiable Conformal Training for LLM Reasoning Factualitycited by 1

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