Title
Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition Arthur Hoarau Benjamin Quost Sébastien Destercke Willem Waegeman UQCV UD PER 82 0 0 30 Jan 2025
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph Roman Vashurin Ekaterina Fadeeva Artem Vazhentsev Akim Tsvigun Daniil Vasilev ... Timothy Baldwin Timothy Baldwin Maxim Panov Artem Shelmanov Artem Shelmanov HILM 68 10 0 21 Jun 2024
Second-Order Uncertainty Quantification: Variance-Based Measures Yusuf Sale Paul Hofman Lisa Wimmer Eyke Hüllermeier Thomas Nagler PER UQCV UD 39 8 0 30 Dec 2023
On the Limitations of Simulating Active Learning Katerina Margatina Nikolaos Aletras 31 11 0 21 May 2023
Investigating Multi-source Active Learning for Natural Language Inference Ard Snijders Douwe Kiela Katerina Margatina 26 7 0 14 Feb 2023
Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement Soyeong Jeong Jinheon Baek Sung Ju Hwang Jong C. Park 29 2 0 10 Feb 2023
Smooth Sailing: Improving Active Learning for Pre-trained Language Models with Representation Smoothness Analysis Josip Jukić Jan Snajder 16 5 0 20 Dec 2022
A Survey of Active Learning for Natural Language Processing Zhisong Zhang Emma Strubell Eduard H. Hovy LM&MA 38 65 0 18 Oct 2022
YATO: Yet Another deep learning based Text analysis Open toolkit Zeqiang Wang Yile Wang Jiageng Wu Zhiyang Teng Jie Yang 40 3 0 28 Sep 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? Lisa Wimmer Yusuf Sale Paul Hofman Bern Bischl Eyke Hüllermeier PER UD 42 65 0 07 Sep 2022
Towards Computationally Feasible Deep Active Learning Akim Tsvigun Artem Shelmanov Gleb Kuzmin Leonid Sanochkin Daniil Larionov Gleb Gusev Manvel Avetisian L. Zhukov 32 15 0 07 May 2022
On the Importance of Effectively Adapting Pretrained Language Models for Active Learning Katerina Margatina Loïc Barrault Nikolaos Aletras 27 36 0 16 Apr 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015