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11/19/2021
Combined Scaling for Zero-shot Transfer Learning
We present a combined scaling method called BASIC that achieves 85.7 zer...
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09/13/2021
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning
Despite their recent successes in tackling many NLP tasks, large-scale p...
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12/15/2020
Pre-Training Transformers as Energy-Based Cloze Models
We introduce Electric, an energy-based cloze model for representation le...
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11/09/2020
Towards Domain-Agnostic Contrastive Learning
Despite recent success, most contrastive self-supervised learning method...
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03/23/2020
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Masked language modeling (MLM) pre-training methods such as BERT corrupt...
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01/27/2020
Towards a Human-like Open-Domain Chatbot
We present Meena, a multi-turn open-domain chatbot trained end-to-end on...
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11/19/2019
A Hybrid Morpheme-Word Representation for Machine Translation of Morphologically Rich Languages
We propose a language-independent approach for improving statistical mac...
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11/11/2019
Self-training with Noisy Student improves ImageNet classification
We present a simple self-training method that achieves 87.4 on ImageNet,...
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10/29/2019
Findings of the Third Workshop on Neural Generation and Translation
This document describes the findings of the Third Workshop on Neural Gen...
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07/10/2019
BAM! Born-Again Multi-Task Networks for Natural Language Understanding
It can be challenging to train multi-task neural networks that outperfor...
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06/07/2019
Selfie: Self-supervised Pretraining for Image Embedding
We introduce a pretraining technique called Selfie, which stands for SEL...
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04/29/2019
Unsupervised Data Augmentation
Despite its success, deep learning still needs large labeled datasets to...
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09/22/2018
Semi-Supervised Sequence Modeling with Cross-View Training
Unsupervised representation learning algorithms such as word2vec and ELM...
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09/19/2018
Latent Topic Conversational Models
Latent variable models have been a preferred choice in conversational mo...
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06/08/2018
Findings of the Second Workshop on Neural Machine Translation and Generation
This document describes the findings of the Second Workshop on Neural Ma...
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04/23/2018
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension
Current end-to-end machine reading and question answering (Q&A) models a...
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10/05/2017
On the Effective Use of Pretraining for Natural Language Inference
Neural networks have excelled at many NLP tasks, but there remain open q...
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07/01/2017
Efficient Attention using a Fixed-Size Memory Representation
The standard content-based attention mechanism typically used in sequenc...
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04/03/2017
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Recurrent neural network models with an attention mechanism have proven ...
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03/11/2017
Massive Exploration of Neural Machine Translation Architectures
Neural Machine Translation (NMT) has shown remarkable progress over the ...
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06/29/2016
Compression of Neural Machine Translation Models via Pruning
Neural Machine Translation (NMT), like many other deep learning domains,...
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04/04/2016
Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models
Nearly all previous work on neural machine translation (NMT) has used qu...
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11/19/2015
Multi-task Sequence to Sequence Learning
Sequence to sequence learning has recently emerged as a new paradigm in ...
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08/17/2015
Effective Approaches to Attention-based Neural Machine Translation
An attentional mechanism has lately been used to improve neural machine ...
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02/28/2015
When Are Tree Structures Necessary for Deep Learning of Representations?
Recursive neural models, which use syntactic parse trees to recursively ...
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10/30/2014
