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ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification

ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification

28 January 2021
Manoj Kumar
Varun Kumar
Hadrien Glaude
Cyprien delichy
Aman Alok
Rahul Gupta
    VLM
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Papers citing "ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification"

4 / 4 papers shown
Title
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with
  Mixture Attention Mechanism
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism
Han Liu
Siyang Zhao
Xiaotong Zhang
Feng Zhang
Ju Sun
Hong Yu
Xianchao Zhang
VLM
31
11
0
05 Jun 2022
Generative Conversational Networks
Generative Conversational Networks
Alexandros Papangelis
Karthik Gopalakrishnan
Aishwarya Padmakumar
Seokhwan Kim
Gokhan Tur
Dilek Z. Hakkani-Tür
21
18
0
15 Jun 2021
Delta-encoder: an effective sample synthesis method for few-shot object
  recognition
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz
Leonid Karlinsky
J. Shtok
Sivan Harary
Mattias Marder
Rogerio Feris
Abhishek Kumar
Raja Giryes
A. Bronstein
186
351
0
12 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
338
11,684
0
09 Mar 2017
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