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Stefan Rueger

2 accepted papers

2024

CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs

UAI 2024poster

Despite the impressive capability of large language models (LLMs), knowing when to trust their generations remains an open challenge. The recent literature on uncertainty quantification of natural language generation (NLG) utilizes a conventional natural language inference (NLI) classifier to measur…

2023

Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration

UAI 2023poster

Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-confidence; i.e., the model’s confidence in its prediction can be greater or less than the model’s accuracy. Recent stud…