TA-CQR adaptively allocates miscoverage tails to produce shortest single-interval conformal prediction sets with exact marginal coverage and provides oracle inequalities for length.
Jing Lei, Max G’Sell, Alessandro Rinaldo, Ryan J Tibshirani, and Larry Wasserman
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
SDM activation and estimator extend softmax with similarity and distance awareness for more robust selective classification in pre-trained language models.
citing papers explorer
-
Tail allocation for conformal prediction intervals
TA-CQR adaptively allocates miscoverage tails to produce shortest single-interval conformal prediction sets with exact marginal coverage and provides oracle inequalities for length.
-
Similarity-Distance-Magnitude Activations
SDM activation and estimator extend softmax with similarity and distance awareness for more robust selective classification in pre-trained language models.