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10/25/2021
The Efficiency Misnomer
Model efficiency is a critical aspect of developing and deploying machin...
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09/22/2021
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers
There remain many open questions pertaining to the scaling behaviour of ...
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04/18/2021
Simple and Efficient ways to Improve REALM
Dense retrieval has been shown to be effective for retrieving relevant d...
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03/23/2021
Scaling Local Self-Attention For Parameter Efficient Visual Backbones
Self-attention has the promise of improving computer vision systems due ...
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01/27/2021
Bottleneck Transformers for Visual Recognition
We present BoTNet, a conceptually simple yet powerful backbone architect...
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03/12/2020
Efficient Content-Based Sparse Attention with Routing Transformers
Self-attention has recently been adopted for a wide range of sequence mo...
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06/13/2019
Stand-Alone Self-Attention in Vision Models
Convolutions are a fundamental building block of modern computer vision ...
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05/29/2019
Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation
Advances in learning and representations have reinvigorated work that co...
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04/22/2019
Attention Augmented Convolutional Networks
Convolutional networks have been the paradigm of choice in many computer...
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11/05/2018
Mesh-TensorFlow: Deep Learning for Supercomputers
Batch-splitting (data-parallelism) is the dominant distributed Deep Neur...
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09/12/2018
An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation
Music relies heavily on self-reference to build structure and meaning. W...
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09/12/2018
Music Transformer
Music relies heavily on repetition to build structure and meaning. Self-...
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06/04/2018
Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, makin...
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05/28/2018
Theory and Experiments on Vector Quantized Autoencoders
Deep neural networks with discrete latent variables offer the promise of...
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03/16/2018
Tensor2Tensor for Neural Machine Translation
Tensor2Tensor is a library for deep learning models that is well-suited ...
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03/09/2018
Fast Decoding in Sequence Models using Discrete Latent Variables
Autoregressive sequence models based on deep neural networks, such as RN...
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03/06/2018
Self-Attention with Relative Position Representations
Relying entirely on an attention mechanism, the Transformer introduced b...
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02/15/2018
Image Transformer
Image generation has been successfully cast as an autoregressive sequenc...
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02/15/2018
Image Tranformer
Image generation has been successfully cast as an autoregressive sequenc...
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06/16/2017
One Model To Learn Them All
Deep learning yields great results across many fields, from speech recog...
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06/12/2017
