Pearls from Pebbles: Improved Confidence Functions for Auto-labeling

Pearls from Pebbles: Improved Confidence Functions for Auto-labeling

24 April 2024

Harit Vishwakarma

Satya Sai Srinath Namburi

Ramya Korlakai Vinayak

Papers citing "Pearls from Pebbles: Improved Confidence Functions for Auto-labeling"

19 / 19 papers shown

Title
ScriptoriumWS: A Code Generation Assistant for Weak Supervision Tzu-Heng Huang Catherine Cao Spencer Schoenberg Harit Vishwakarma Nicholas Roberts Frederic Sala NoLa 197 6 0 17 Feb 2025
Taming False Positives in Out-of-Distribution Detection with Human Feedback Harit Vishwakarma Heguang Lin Ramya Korlakai Vinayak OODD 49 6 0 25 Apr 2024
Mitigating Source Bias for Fairer Weak Supervision Changho Shin Sonia Cromp Dyah Adila Frederic Sala 44 2 0 30 Mar 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 83 41 0 06 Mar 2023
Lifting Weak Supervision To Structured Prediction Harit Vishwakarma Nicholas Roberts Frederic Sala NoLa 58 8 0 24 Nov 2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration Thomas Joy Francesco Pinto Ser-Nam Lim Philip Torr P. Dokania UQCV 66 34 0 13 Jul 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 229 1,149 0 07 Jul 2021
Distribution-free calibration guarantees for histogram binning without sample splitting Chirag Gupta Aaditya Ramdas 64 39 0 10 May 2021
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach Yue Yu Simiao Zuo Haoming Jiang Wendi Ren T. Zhao Chao Zhang AI4MH 48 133 0 15 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 192 1,349 0 03 Oct 2020
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods Daniel Y. Fu Mayee F. Chen Frederic Sala Sarah Hooper Kayvon Fatahalian Christopher Ré OffRL 84 115 0 27 Feb 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 81 463 0 21 Feb 2020
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 164 356 0 23 Sep 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 195 1,950 0 06 Jun 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 167 558 0 13 Dec 2018
Selective Classification for Deep Neural Networks Yonatan Geifman Ran El-Yaniv CVBM 95 527 0 23 May 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 158 3,454 0 07 Oct 2016
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 161 3,271 0 05 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,918 1 21 Dec 2013