conftrace_

predictive uncertainty

79 papers

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Also known as

PU

Co-occurring keywords

uncertainty quantification (1393) uncertainty estimation (648) out-of-distribution detection (617) variational inference (2069) neural network (6616) model calibration (232) bayesian deep learning (68) bayesian neural network (201) epistemic uncertainty (160) uncertainty calibration (58)

Papers

GUIDER: Uncertainty Guided Dynamic Re-ranking for Large Language Models Based Recommender Systems AAAI 2026
What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning ACL 2026
Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood WACV 2026
Continuum Dropout for Neural Differential Equations AAAI 2026
Uncertainty Unveiled: Can Exposure to More In-context Examples Mitigate Uncertainty for Large Language Models? ACL 2025
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation CVPR 2025
Label Calibration in Source Free Domain Adaptation WACV 2025
Measuring Label Ambiguity in Subjective Tasks using Predictive Uncertainty Estimation ACL 2025
Syntax-Aware Retrieval Augmentation for Neural Symbolic Regression EMNLP 2025
Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework EMNLP 2024
Piecewise Linear Transformation – Propagating Aleatoric Uncertainty in Neural Networks AAAI 2024
Generalized Measures of Anticipation and Responsivity in Online Language Processing EMNLP 2024
Density Uncertainty Layers for Reliable Uncertainty Estimation AISTATS 2024
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NIPS 2024
Uncertainty-aware Action Decoupling Transformer for Action Anticipation CVPR 2024
Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models ACL 2024
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks IJCAI 2024
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study EMNLP 2023
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models UAI 2023
Knowledge Distillation ≈ Label Smoothing: Fact or Fallacy? EMNLP 2023
NPCL: Neural Processes for Uncertainty-Aware Continual Learning NIPS 2023
Probabilistic Imputation for Time-series Classification with Missing Data ICML 2023
Federated Learning with Uncertainty via Distilled Predictive Distributions ACML 2023
Variational Boosted Soft Trees AISTATS 2023
Aligning Predictive Uncertainty with Clarification Questions in Grounded Dialog EMNLP 2023