ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2311.09358
  4. Cited By
Empirical evaluation of Uncertainty Quantification in
  Retrieval-Augmented Language Models for Science

Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science

15 November 2023
S. Wagle
Sai Munikoti
Anurag Acharya
Sara Smith
Sameera Horawalavithana
ArXivPDFHTML

Papers citing "Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science"

3 / 3 papers shown
Title
Uncertainty Quantification with Pre-trained Language Models: A
  Large-Scale Empirical Analysis
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis
Yuxin Xiao
Paul Pu Liang
Umang Bhatt
W. Neiswanger
Ruslan Salakhutdinov
Louis-Philippe Morency
173
86
0
10 Oct 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
249
9,134
0
06 Jun 2015
1