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. 2212.09171
  4. Cited By
Rainproof: An Umbrella To Shield Text Generators From
  Out-Of-Distribution Data

Rainproof: An Umbrella To Shield Text Generators From Out-Of-Distribution Data

18 December 2022
Maxime Darrin
Pablo Piantanida
Pierre Colombo
    OODD
ArXivPDFHTML

Papers citing "Rainproof: An Umbrella To Shield Text Generators From Out-Of-Distribution Data"

10 / 10 papers shown
Title
Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home
Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home
Viktor Moskvoretskii
M. Lysyuk
Mikhail Salnikov
Nikolay Ivanov
Sergey Pletenev
Daria Galimzianova
Nikita Krayko
Vasily Konovalov
Irina Nikishina
Alexander Panchenko
RALM
68
4
0
24 Feb 2025
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
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
64
8
0
21 Jun 2024
WeiPer: OOD Detection using Weight Perturbations of Class Projections
WeiPer: OOD Detection using Weight Perturbations of Class Projections
Maximilian Granz
Manuel Heurich
Tim Landgraf
OODD
32
1
0
27 May 2024
Toward Stronger Textual Attack Detectors
Toward Stronger Textual Attack Detectors
Pierre Colombo
Marine Picot
Nathan Noiry
Guillaume Staerman
Pablo Piantanida
28
5
0
21 Oct 2023
Beam Search with Bidirectional Strategies for Neural Response Generation
Beam Search with Bidirectional Strategies for Neural Response Generation
Pierre Colombo
Chouchang Yang
Giovanna Varni
Chloé Clavel
30
13
0
07 Oct 2021
On the Importance of Gradients for Detecting Distributional Shifts in
  the Wild
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang
Andrew Geng
Yixuan Li
173
324
0
01 Oct 2021
Types of Out-of-Distribution Texts and How to Detect Them
Types of Out-of-Distribution Texts and How to Detect Them
Udit Arora
William Huang
He He
OODD
207
97
0
14 Sep 2021
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain
  Detection
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection
Alexander Podolskiy
Dmitry Lipin
A. Bout
Ekaterina Artemova
Irina Piontkovskaya
OODD
84
82
0
11 Jan 2021
The Tatoeba Translation Challenge -- Realistic Data Sets for Low
  Resource and Multilingual MT
The Tatoeba Translation Challenge -- Realistic Data Sets for Low Resource and Multilingual MT
Jörg Tiedemann
160
163
0
13 Oct 2020
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,231
0
24 Jun 2017
1