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08/15/2023
RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models
In this paper, we investigate the in-context learning ability of retriev...
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11/02/2022
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Large-scale diffusion-based generative models have led to breakthroughs ...
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06/09/2022
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
Despite recent progress in generative adversarial network(GAN)-based voc...
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05/14/2022
PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning
In this work, we present a reinforcement learning (RL) based approach to...
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05/10/2022
Reducing Activation Recomputation in Large Transformer Models
Training large transformer models is one of the most important computati...
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01/28/2022
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model
Pretrained general-purpose language models can achieve state-of-the-art ...
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07/05/2021
Long-Short Transformer: Efficient Transformers for Language and Vision
Transformers have achieved success in both language and vision domains. ...
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04/09/2021
Efficient Large-Scale Language Model Training on GPU Clusters
Large language models have led to state-of-the-art accuracies across a r...
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09/21/2020
DiffWave: A Versatile Diffusion Model for Audio Synthesis
In this work, we propose DiffWave, a versatile Diffusion probabilistic m...
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05/21/2020
Hierarchical Multi-Scale Attention for Semantic Segmentation
Multi-scale inference is commonly used to improve the results of semanti...
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02/22/2020
Training Question Answering Models From Synthetic Data
Question and answer generation is a data augmentation method that aims t...
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10/28/2019
Few-shot Video-to-Video Synthesis
Video-to-video synthesis (vid2vid) aims at converting an input semantic ...
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09/26/2019
Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning
We present GQSAT, a branching heuristic in a Boolean SAT solver trained ...
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09/17/2019
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
Recent work in unsupervised language modeling demonstrates that training...
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09/17/2019
Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism
Recent work in unsupervised language modeling demonstrates that training...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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08/20/2018
Video-to-Video Synthesis
We study the problem of video-to-video synthesis, whose goal is to learn...
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12/08/2015
