Bryan Catanzaro

research

∙ 09/12/2023

CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram

In this work, we present CleanUNet 2, a speech denoising model that comb...

0 Zhifeng Kong, et al. ∙

research

∙ 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...

0 Jie Huang, et al. ∙

research

∙ 08/07/2023

GraPhSyM: Graph Physical Synthesis Model

In this work, we introduce GraPhSyM, a Graph Attention Network (GATv2) m...

0 Ahmed Agiza, et al. ∙

research

∙ 04/13/2023

Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study

Large decoder-only language models (LMs) can be largely improved in term...

16 Boxin Wang, et al. ∙

research

∙ 02/14/2023

Adding Instructions during Pretraining: Effective Way of Controlling Toxicity in Language Models

Pretrained large language models have become indispensable for solving v...

0 Shrimai Prabhumoye, et al. ∙

research

∙ 02/09/2023

Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning

Augmenting pretrained language models (LMs) with a vision encoder (e.g.,...

0 Zhuolin Yang, et al. ∙

research

∙ 01/24/2023

Multilingual Multiaccented Multispeaker TTS with RADTTS

We work to create a multilingual speech synthesis system which can gener...

0 Rohan Badlani, et al. ∙

research

∙ 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 ...

0 Yogesh Balaji, et al. ∙

research

∙ 10/25/2022

Evaluating Parameter Efficient Learning for Generation

Parameter efficient learning methods (PERMs) have recently gained signif...

0 Peng Xu, et al. ∙

research

∙ 10/12/2022

Context Generation Improves Open Domain Question Answering

Closed-book question answering (QA) requires a model to directly answer ...

12 Dan Su, et al. ∙

research

∙ 06/09/2022

BigVGAN: A Universal Neural Vocoder with Large-Scale Training

Despite recent progress in generative adversarial network(GAN)-based voc...

8 Sang-gil Lee, et al. ∙

research

∙ 06/09/2022

Factuality Enhanced Language Models for Open-Ended Text Generation

Pretrained language models (LMs) are susceptible to generate text with n...

2 Nayeon Lee, et al. ∙

research

∙ 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...

0 Rajarshi Roy, et al. ∙

research

∙ 05/10/2022

Reducing Activation Recomputation in Large Transformer Models

Training large transformer models is one of the most important computati...

0 Vijay Korthikanti, et al. ∙

research

∙ 03/16/2022

Multi-Stage Prompting for Knowledgeable Dialogue Generation

Existing knowledge-grounded dialogue systems typically use finetuned ver...

0 Zihan Liu, et al. ∙

research

∙ 03/03/2022

Generative Modeling for Low Dimensional Speech Attributes with Neural Spline Flows

Despite recent advances in generative modeling for text-to-speech synthe...

0 Kevin J. Shih, et al. ∙

research

∙ 02/15/2022

Speech Denoising in the Waveform Domain with Self-Attention

In this work, we present CleanUNet, a causal speech denoising model on t...

6 Zhifeng Kong, et al. ∙

research

∙ 02/08/2022

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models

Pre-trained language models (LMs) are shown to easily generate toxic lan...

16 Boxin Wang, et al. ∙

research

∙ 01/31/2022

Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction

Video compression is a central feature of the modern internet powering t...

0 Max Ehrlich, et al. ∙

research

∙ 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 ...

8 Shaden Smith, et al. ∙

research

∙ 12/15/2021

Few-shot Instruction Prompts for Pretrained Language Models to Detect Social Biases

Detecting social bias in text is challenging due to nuance, subjectivity...

22 Shrimai Prabhumoye, et al. ∙

research

∙ 09/06/2021

Guiding Global Placement With Reinforcement Learning

Recent advances in GPU accelerated global and detail placement have redu...

0 Robert Kirby, et al. ∙

research

∙ 08/23/2021

One TTS Alignment To Rule Them All

Speech-to-text alignment is a critical component of neural textto-speech...

0 Rohan Badlani, et al. ∙

research

∙ 07/05/2021

Long-Short Transformer: Efficient Transformers for Language and Vision

Transformers have achieved success in both language and vision domains. ...

12 Chen Zhu, et al. ∙

research

∙ 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...

8 Deepak Narayanan, et al. ∙

research

∙ 01/02/2021

End-to-End Training of Neural Retrievers for Open-Domain Question Answering

Recent work on training neural retrievers for open-domain question answe...

0 Devendra Singh Sachan, et al. ∙

research

∙ 10/20/2020

Local Knowledge Powered Conversational Agents

State-of-the-art conversational agents have advanced significantly in co...

0 Sashank Santhanam, et al. ∙

research

∙ 10/02/2020

MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models

Existing pre-trained large language models have shown unparalleled gener...

0 Peng Xu, et al. ∙

research

∙ 09/21/2020

DiffWave: A Versatile Diffusion Model for Audio Synthesis

In this work, we propose DiffWave, a versatile Diffusion probabilistic m...

9 Zhifeng Kong, et al. ∙

research

∙ 07/14/2020

Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

Conventional CNNs for texture synthesis consist of a sequence of (de)-co...

2 Guilin Liu, et al. ∙

research

∙ 05/21/2020

Hierarchical Multi-Scale Attention for Semantic Segmentation

Multi-scale inference is commonly used to improve the results of semanti...

20 Andrew Tao, et al. ∙

research

∙ 05/13/2020

Large Scale Multi-Actor Generative Dialog Modeling

Non-goal oriented dialog agents (i.e. chatbots) aim to produce varying a...

0 Alex Boyd, et al. ∙

research

∙ 05/12/2020

Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis

generative network for text-to-speech synthesis with control over speec...

0 Rafael Valle, et al. ∙

research

∙ 02/22/2020

Training Question Answering Models From Synthetic Data

Question and answer generation is a data augmentation method that aims t...

16 Raul Puri, et al. ∙

research

∙ 01/26/2020

Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos

Unsupervised landmark learning is the task of learning semantic keypoint...

25 Aysegul Dundar, et al. ∙

research

∙ 12/25/2019

Neural ODEs for Image Segmentation with Level Sets

We propose a novel approach for image segmentation that combines Neural ...

6 Rafael Valle, et al. ∙

research

∙ 12/10/2019

Zero-shot Text Classification With Generative Language Models

This work investigates the use of natural language to enable zero-shot m...

0 Raul Puri, et al. ∙

research

∙ 10/28/2019

Few-shot Video-to-Video Synthesis

Video-to-video synthesis (vid2vid) aims at converting an input semantic ...

14 Ting-Chun Wang, et al. ∙

research

∙ 10/26/2019

Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens

Mellotron is a multispeaker voice synthesis model based on Tacotron 2 GS...

0 Rafael Valle, et al. ∙

research

∙ 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 ...

37 Vitaly Kurin, et al. ∙

research

∙ 09/17/2019

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Recent work in unsupervised language modeling demonstrates that training...

0 Mohammad Shoeybi, et al. ∙

research

∙ 09/17/2019

Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism

Recent work in unsupervised language modeling demonstrates that training...

0 Mohammad Shoeybi, et al. ∙

research

∙ 09/06/2019

Video Interpolation and Prediction with Unsupervised Landmarks

Prediction and interpolation for long-range video data involves the comp...

1 Kevin J. Shih, et al. ∙

research

∙ 06/13/2019

Unsupervised Video Interpolation Using Cycle Consistency

Learning to synthesize high frame rate videos via interpolation requires...

1 Fitsum A. Reda, et al. ∙

research

∙ 03/29/2019

SysML: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoptio...

0 Alexander Ratner, et al. ∙

research

∙ 03/07/2019

Graphical Contrastive Losses for Scene Graph Generation

Most scene graph generators use a two-stage pipeline to detect visual re...

10 Ji Zhang, et al. ∙

research

∙ 12/04/2018

Improving Semantic Segmentation via Video Propagation and Label Relaxation

Semantic segmentation requires large amounts of pixel-wise annotations t...

0 Yi Zhu, et al. ∙

research

∙ 12/04/2018

Practical Text Classification With Large Pre-Trained Language Models

Multi-emotion sentiment classification is a natural language processing ...

0 Neel Kant, et al. ∙

research

∙ 11/28/2018

Partial Convolution based Padding

In this paper, we present a simple yet effective padding scheme that can...

6 Guilin Liu, et al. ∙

research

∙ 11/21/2018

An Interpretable Model for Scene Graph Generation

We propose an efficient and interpretable scene graph generator. We cons...

0 Ji Zhang, et al. ∙

Bryan Catanzaro

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