WARP
NLP Task Adaptation
An approach to transfer learning for NLP tasks using adversarial reprogramming and word-level task-specific embeddings.
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming GPT-3 on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/
83 stars
8 watching
16 forks
Language: Python
last commit: about 3 years ago adversarialfew-shot-learningnatural-language-processingpretrained-models
Related projects:
| Repository | Description | Stars |
|---|---|---|
 wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 849 |
 paarthneekhara/rnn_adversarial_reprogramming | Repurposes pre-trained neural networks for new classification tasks through adversarial reprogramming of their inputs. | 6 |
 prinsphield/adversarial_reprogramming | This project enables reprogramming of pre-trained neural networks to work on new tasks by fine-tuning them on smaller datasets. | 33 |
 arunmallya/piggyback | Adapting a single network to multiple tasks by learning to mask weights | 182 |
 tristandeleu/pytorch-maml-rl | Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks | 827 |
 dodohow1011/speechadvreprogram | Developing low-resource speech command recognition systems using adversarial reprogramming and transfer learning | 18 |
 layneh/self-adaptive-training | Improves deep network generalization under noise and enhances self-supervised representation learning | 127 |
 sandeep42/anuvada | This is an open source PyTorch library providing tools and models to explain the predictions of deep neural networks for natural language processing tasks. | 19 |
 namisan/mt-dnn | A PyTorch package implementing multi-task deep neural networks for natural language understanding | 2,238 |
 rguthrie3/deeplearningfornlpinpytorch | A comprehensive tutorial on deep learning for natural language processing with PyTorch, covering the basics and advancing to linguistic structure prediction. | 1,940 |
 guillaume-chevalier/sgnn-self-governing-neural-networks-projection-layer | Reproduces a SGNN's word projections preprocessing pipeline using word n-grams instead of skip-grams | 23 |
 graal-research/poutyne | A PyTorch framework simplifying neural network training with automated boilerplate code and callback utilities | 569 |
 akanimax/pro_gan_pytorch | Implementation of a deep learning model for generating high-quality images with improved stability and variation. | 536 |
 ashawkey/torch-ngp | A PyTorch implementation of NeRF (Neural Radiance Fields) and related techniques for 3D rendering and reconstruction | 2,112 |
 l0sg/relational-rnn-pytorch | An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch for word language modeling | 244 |