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. 2111.00506
  4. Cited By
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug
  andPlay Data Augmentation

PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation

31 October 2021
Mrinal Rawat
R. Hebbalaguppe
L. Vig
    OODD
ArXivPDFHTML

Papers citing "PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation"

6 / 6 papers shown
Title
Classical Out-of-Distribution Detection Methods Benchmark in Text
  Classification Tasks
Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks
M. Baran
Joanna Baran
Mateusz Wójcik
Maciej Ziȩba
Adam Gonczarek
OODD
54
4
0
13 Jul 2023
OOD-DiskANN: Efficient and Scalable Graph ANNS for Out-of-Distribution
  Queries
OOD-DiskANN: Efficient and Scalable Graph ANNS for Out-of-Distribution Queries
Shikhar Jaiswal
Ravishankar Krishnaswamy
Ankit Garg
H. Simhadri
Sheshansh Agrawal
23
23
0
22 Oct 2022
Out-of-Distribution Detection and Selective Generation for Conditional
  Language Models
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Jie Jessie Ren
Jiaming Luo
Yao-Min Zhao
Kundan Krishna
Mohammad Saleh
Balaji Lakshminarayanan
Peter J. Liu
OODD
75
98
0
30 Sep 2022
Constraining Representations Yields Models That Know What They Don't
  Know
Constraining Representations Yields Models That Know What They Don't Know
João Monteiro
Pau Rodríguez López
Pierre-Andre Noel
I. Laradji
David Vazquez
AAML
44
0
0
30 Aug 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
278
5,695
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
287
9,167
0
06 Jun 2015
1