Joint Energy-based Model Training for Better Calibrated Natural Language
Understanding Models

Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models

18 January 2021

Tianxing He

Ehsan Hosseini-Asl

Papers citing "Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models"

8 / 8 papers shown

Title
LSEBMCL: A Latent Space Energy-Based Model for Continual Learning Xiaodi Li Dingcheng Li Rujun Gao Mahmoud Zamani Latifur Khan CLL KELM 54 0 0 09 Jan 2025
Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models Guande He Jianfei Chen Jun Zhu 45 20 0 30 May 2023
Exploring Energy-based Language Models with Different Architectures and Training Methods for Speech Recognition Hong Liu Z. Lv Zhijian Ou Wenbo Zhao Qing Xiao 24 0 0 22 May 2023
Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates Dongfang Li Baotian Hu Qingcai Chen 16 8 0 06 Nov 2022
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions C. Ekbote Moksh Jain Payel Das Yoshua Bengio 44 4 0 01 Nov 2022
EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering Violetta Shevchenko Ehsan Abbasnejad A. Dick Anton Van Den Hengel Damien Teney 49 0 0 29 Jun 2022
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting Tomasz Korbak Hady ElSahar Germán Kruszewski Marc Dymetman CLL 27 51 0 01 Jun 2022
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 304 7,005 0 20 Apr 2018