Uncertainty-Aware Natural Language Inference with Stochastic Weight
Averaging

Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging

10 April 2023

Markus Heinonen

Jörg Tiedemann

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Papers citing "Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging"

18 / 18 papers shown

Title
Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization Yue Zhang Liqiang Jing Vibhav Gogate 186 4 0 19 Dec 2024
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging Peng Lu I. Kobyzev Mehdi Rezagholizadeh Ahmad Rashid A. Ghodsi Philippe Langlais MoMe 87 11 0 12 Dec 2022
The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation Barbara Plank 80 100 0 04 Nov 2022
Revisiting Checkpoint Averaging for Neural Machine Translation Yingbo Gao Christian Herold Zijian Yang Hermann Ney MoMe 134 12 0 21 Oct 2022
When Do Flat Minima Optimizers Work? Jean Kaddour Linqing Liu Ricardo M. A. Silva Matt J. Kusner ODL 102 64 0 01 Feb 2022
How Emotionally Stable is ALBERT? Testing Robustness with Stochastic Weight Averaging on a Sentiment Analysis Task Urja Khurana Eric T. Nalisnick Antske Fokkens MoMe 65 6 0 18 Nov 2021
What Can We Learn from Collective Human Opinions on Natural Language Inference Data? Yixin Nie Xiang Zhou Joey Tianyi Zhou 93 138 0 07 Oct 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 132 656 0 20 Feb 2020
Uncertain Natural Language Inference Tongfei Chen Zhengping Jiang Adam Poliak Keisuke Sakaguchi Benjamin Van Durme UQLM 78 58 0 06 Sep 2019
Human uncertainty makes classification more robust Joshua C. Peterson Ruairidh M. Battleday Thomas Griffiths Olga Russakovsky OOD 64 306 0 19 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 700 24,572 0 26 Jul 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 109 809 0 07 Feb 2019
Testing the Generalization Power of Neural Network Models Across NLI Benchmarks Aarne Talman S. Chatzikyriakidis ELM 76 48 0 23 Oct 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 1.1K 7,201 0 20 Apr 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 143 1,673 0 14 Mar 2018
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 524 4,497 0 18 Apr 2017
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 338 4,297 0 21 Aug 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 891 9,364 0 06 Jun 2015