R-Tuning: Teaching Large Language Models to Refuse Unknown Questions
Paper
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2311.09677
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Published
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3
Uncertainty
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Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models
Paper • 2307.10236 • Published • 1 -
Shifting Attention to Relevance: Towards the Uncertainty Estimation of Large Language Models
Paper • 2307.01379 • Published • 1 -
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Paper • 2305.19187 • Published • 1 -
Quantifying lottery tickets under label noise: accuracy, calibration, and complexity
Paper • 2306.12190 • Published • 1 -
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
Paper • 2305.14975 • Published • 1 -
PAC Neural Prediction Set Learning to Quantify the Uncertainty of Generative Language Models
Paper • 2307.09254 • Published • 1 -
Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models
Paper • 2305.13712 • Published • 2