mlsanityData to 14 Oct 2026

Decoding Uncertainty: The Impact of Decoding Strategies for Uncertainty Estimation in Large Language Models

arXiv 2509.16696 ↗First posted 20 Sep 2025cs.CL cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

Decoding strategies manipulate the probability distribution underlying the output of a language model and can therefore affect both generation quality and its uncertainty. In this study, we investigate the impact of decoding strategies on uncertainty estimation in Large Language Models (LLMs). Our experiments show that Contrastive Search, which mitigates repetition, yields better uncertainty estimates on average across a range of preference-aligned LLMs. In contrast, the benefits of these strategies sometimes diverge when the model is only post-trained with supervised fine-tuning, i.e. without explicit alignment.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 35 of its 54 references that are in the map. First posted on arXiv 20 Sep 2025.

Builds on

35 of 54 references.

References · 35

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2017Proximal Policy Optimization Algorithmscited by 15,215
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  5. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  6. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  7. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,224
  8. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
  9. 2019The Curious Case of Neural Text Degenerationcited by 2,916
  10. 2023MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIcited by 2,080
  11. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,317
  12. 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,077
23 more
  1. 2020COMET: A Neural Framework for MT Evaluationcited by 1,033
  2. 2023Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedbackcited by 812
  3. 2022Contrastive Decoding: Open-ended Text Generation as Optimizationcited by 609
  4. 2023Zephyr: Direct Distillation of LM Alignmentcited by 506
  5. 2023AlignScore: Evaluating Factual Consistency with a Unified Alignment Functioncited by 288
  6. 2017Beam Search Strategies for Neural Machine Translationcited by 232
  7. 2022A Contrastive Framework for Neural Text Generationcited by 225
  8. 2023LM-Polygraph: Uncertainty Estimation for Language Modelscited by 131
  9. 2024A Thorough Examination of Decoding Methods in the Era of LLMscited by 114
  10. 2018Bias-Reduced Uncertainty Estimation for Deep Neural Classifierscited by 113
  11. 2024Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraphcited by 105
  12. 2019Calibration of Encoder Decoder Models for Neural Machine Translationcited by 68
  13. 2022Contrastive Search Is What You Need For Neural Text Generationcited by 59
  14. 2024Calibrating Language Models with Adaptive Temperature Scalingcited by 58
  15. 2023What Can We Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifierscited by 35
  16. 2024Improving Uncertainty Estimation through Semantically Diverse Language Generationcited by 35
  17. 2022Detection of Word Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimationcited by 32
  18. 2024mHumanEval -- A Multilingual Benchmark to Evaluate Large Language Models for Code Generationcited by 32
  19. 2023A Frustratingly Simple Decoding Method for Neural Text Generationcited by 16
  20. 2024Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domaincited by 9
  21. 2024Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?cited by 3
  22. 2024Trust & Safety of LLMs and LLMs in Trust & Safetycited by 3
  23. 2024Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Taskscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2026The Alignment Tax: Response Homogenization in Aligned LLMs and Its Implications for Uncertainty Estimationcited by 4
  2. 2025Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Searchcited by 3
  3. 2026Task-Aware Calibration: Provably Optimal Decoding in LLMscited by 0