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cs.LG2026
The Radio-Frequency Transformer for Signal Separation
Egor Lifar, Semyon Savkin, Rachana Madhukara +3
We study a problem of signal separation: estimating a signal of interest (SOI) contaminated by an unknown non-Gaussian background/interference. Given the training data consisting o…
cs.LG2024
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
Maohao Shen, J. Jon Ryu, Soumya Ghosh +4
This paper questions the effectiveness of a modern predictive uncertainty quantification approach, called \emph{evidential deep learning} (EDL), in which a single neural network mo…
cs.LG2024
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald +3
We consider the issue of calibration in large language models (LLM). Recent studies have found that common interventions such as instruction tuning often result in poorly calibrate…