Efficient Conformal Prediction via Cascaded Inference with Expanded Admission

By Adam Fisch, Tal Schuster, Tommi S. Jaakkola, Regina Barzilay. 2021

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In Statistical Learning Theory

Citations in the corpus

Consistent Accelerated Inference via Confident Adaptive Transformers (2021, methodology): “[8] Adam Fisch, Tal Schuster, Tommi Jaakkola, and Regina Barzilay.”
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence (2021, methodology): “For NEI claims, we randomly sample neutral evidence from the article with the highest BM25 score (Fisch et al., 2021).”
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification (2021, background): “One compelling use-case of conformal prediction is speeding up and decreasing the computational cost of the test-time evaluation of complex models [98, 99].”
Conformal Risk Control (2022, background): “Split conformal prediction [1, 2], which we will henceforth refer to simply as “conformal prediction,” has been useful in areas such as computer vision [3] and natural language processing [4] to provide such a guarantee.”
Few-shot Conformal Prediction with Auxiliary Tasks (2021, background): “…conformal prediction in the context of various validity conditions, such as conditional, risk-controlling, admissible, or equalized coverage (Chernozhukov et al., 2019; Cauchois et al., 2020; Kivaranovic et al., 2020; Romano et al., 2019; 2020; Bates et al., 2020; Fisch et al., 2021, inter alia).”
Confident Adaptive Language Modeling (2022, methodology): “Several methods were developed in recent studies to expand and adjust the theoretical framework for obtaining practical efficiency gains on target applications [4; 7; 21; 26; 27; 48; 88].”