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Vector-Quantized Input-Contextualized Soft Prompts for Natural Language
  Understanding

Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding

23 May 2022
Rishabh Bhardwaj
Amrita Saha
S. Hoi
Soujanya Poria
    VLM
    VPVLM
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Papers citing "Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding"

4 / 4 papers shown
Title
LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based
  on Prompt Tuning of T5
LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5
Chengwei Qin
Shafiq R. Joty
CLL
178
98
0
14 Oct 2021
Disentangling Generative Factors in Natural Language with Discrete
  Variational Autoencoders
Disentangling Generative Factors in Natural Language with Discrete Variational Autoencoders
Giangiacomo Mercatali
André Freitas
CoGe
DRL
46
23
0
15 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,848
0
18 Apr 2021
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
258
1,589
0
21 Jan 2020
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