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Implementation code for the paper "Generating Natural Language Adversarial Examples"
The official implementation of paper U-Net: Machine Reading Comprehension with Unanswerable Questions.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
bkgoksel / UNet
Forked from FudanNLP/UNetImplementation of paper U-Net: Machine Reading Comprehension with Unanswerable Questions.
Utilities, Baselines, Statistics and Descriptions Related to the MSMARCO DATASET
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Python library to easily log experiments and parallelize hyperparameter search for neural networks
Models, data loaders and abstractions for language processing, powered by PyTorch
Applying GANs in improving question generation and answering
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
A modular configuration of Vim and Neovim
A collaborative platform for reproducible research (web interface and CLI).
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
WebNav: A New Large-Scale Task for Natural Language based Sequential Decision Making
Tame the Web MIDI API. Send and receive MIDI messages with ease. Control instruments with user-friendly functions (playNote, sendPitchBend, etc.). React to MIDI input with simple event listeners (n…
The most cited deep learning papers
Question answering dataset featured in "Teaching Machines to Read and Comprehend
Task generation for testing text understanding and reasoning