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09/20/2023
Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation
Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be...
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09/07/2023
REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation
Fully-test-time adaptation (F-TTA) can mitigate performance loss due to ...
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09/06/2023
Robotic Table Tennis: A Case Study into a High Speed Learning System
We present a deep-dive into a real-world robotic learning system that, i...
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06/05/2023
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Autoregressive models for text sometimes generate repetitive and low-qua...
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11/11/2022
Continuous Soft Pseudo-Labeling in ASR
Continuous pseudo-labeling (PL) algorithms such as slimIPL have recently...
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11/02/2022
More Speaking or More Speakers?
Self-training (ST) and self-supervised learning (SSL) methods have demon...
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10/17/2022
Continuous Pseudo-Labeling from the Start
Self-training (ST), or pseudo-labeling has sparked significant interest ...
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07/15/2022
Position Prediction as an Effective Pretraining Strategy
Transformers have gained increasing popularity in a wide range of applic...
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07/05/2022
Efficient Representation Learning via Adaptive Context Pooling
Self-attention mechanisms model long-range context by using pairwise att...
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05/07/2020
RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions
In recent years, all-neural end-to-end approaches have obtained state-of...
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03/31/2020
Robotic Table Tennis with Model-Free Reinforcement Learning
We propose a model-free algorithm for learning efficient policies capabl...
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02/20/2020
Imputer: Sequence Modelling via Imputation and Dynamic Programming
This paper presents the Imputer, a neural sequence model that generates ...
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12/13/2019
SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong
We introduce a new high resolution, high frame rate stereo video dataset...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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11/30/2018
Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play
Training robots with physical bodies requires developing new methods and...
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08/20/2018
Peptide-Spectra Matching from Weak Supervision
As in many other scientific domains, we face a fundamental problem when ...
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12/16/2017
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
This paper describes Tacotron 2, a neural network architecture for speec...
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12/05/2017
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Attention-based encoder-decoder architectures such as Listen, Attend, an...
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11/20/2017
Speech recognition for medical conversations
In this paper we document our experiences with developing speech recogni...
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06/16/2017
An online sequence-to-sequence model for noisy speech recognition
Generative models have long been the dominant approach for speech recogn...
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05/16/2017
Learning Hard Alignments with Variational Inference
There has recently been significant interest in hard attention models fo...
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05/14/2017
Discrete Sequential Prediction of Continuous Actions for Deep RL
It has long been assumed that high dimensional continuous control proble...
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03/29/2017
Tacotron: Towards End-to-End Speech Synthesis
A text-to-speech synthesis system typically consists of multiple stages,...
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03/24/2017
Sequence-to-Sequence Models Can Directly Translate Foreign Speech
We present a recurrent encoder-decoder deep neural network architecture ...
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12/08/2016
Towards better decoding and language model integration in sequence to sequence models
The recently proposed Sequence-to-Sequence (seq2seq) framework advocates...
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10/31/2016
RNN Approaches to Text Normalization: A Challenge
This paper presents a challenge to the community: given a large corpus o...
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10/10/2016
Latent Sequence Decompositions
We present the Latent Sequence Decompositions (LSD) framework. LSD decom...
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10/10/2016
Very Deep Convolutional Networks for End-to-End Speech Recognition
Sequence-to-sequence models have shown success in end-to-end speech reco...
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08/03/2016
Learning Online Alignments with Continuous Rewards Policy Gradient
Sequence-to-sequence models with soft attention had significant success ...
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05/08/2016
Chained Predictions Using Convolutional Neural Networks
In this paper, we present an adaptation of the sequence-to-sequence mode...
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11/18/2015
Adversarial Autoencoders
In this paper, we propose the "adversarial autoencoder" (AAE), which is ...
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11/16/2015
A Neural Transducer
Sequence-to-sequence models have achieved impressive results on various ...
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09/04/2015
Object Recognition from Short Videos for Robotic Perception
Deep neural networks have become the primary learning technique for obje...
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08/05/2015
Listen, Attend and Spell
We present Listen, Attend and Spell (LAS), a neural network that learns ...
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06/09/2015
Pointer Networks
We introduce a new neural architecture to learn the conditional probabil...
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06/09/2015
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Recurrent Neural Networks can be trained to produce sequences of tokens ...
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04/03/2015
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
Learning long term dependencies in recurrent networks is difficult due t...
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12/22/2014
Occlusion Edge Detection in RGB-D Frames using Deep Convolutional Networks
Occlusion edges in images which correspond to range discontinuity in the...
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06/04/2014