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07/18/2023
Llama 2: Open Foundation and Fine-Tuned Chat Models
In this work, we develop and release Llama 2, a collection of pretrained...
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04/19/2023
A Theory on Adam Instability in Large-Scale Machine Learning
We present a theory for the previously unexplained divergent behavior no...
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04/18/2023
UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining
Pretrained multilingual large language models have typically used heuris...
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12/20/2022
Character-Aware Models Improve Visual Text Rendering
Current image generation models struggle to reliably produce well-formed...
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10/24/2022
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners
Large language models (LLM) trained using the next-token-prediction obje...
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10/08/2022
Understanding HTML with Large Language Models
Large language models (LLMs) have shown exceptional performance on a var...
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07/21/2022
Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?
There have been a lot of interest in the scaling properties of Transform...
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04/05/2022
PaLM: Scaling Language Modeling with Pathways
Large language models have been shown to achieve remarkable performance ...
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03/31/2022
Scaling Up Models and Data with and
Recent neural network-based language models have benefited greatly from ...
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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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05/28/2021
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Most widely-used pre-trained language models operate on sequences of tok...
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02/23/2021
Do Transformer Modifications Transfer Across Implementations and Applications?
The research community has proposed copious modifications to the Transfo...
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10/09/2020
On Task-Level Dialogue Composition of Generative Transformer Model
Task-oriented dialogue systems help users accomplish tasks such as booki...
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04/30/2020
WT5?! Training Text-to-Text Models to Explain their Predictions
Neural networks have recently achieved human-level performance on variou...
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10/31/2019
Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning
Task-oriented dialog presents a difficult challenge encompassing multipl...
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10/23/2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Transfer learning, where a model is first pre-trained on a data-rich tas...
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12/01/2017
Deep Learning Scaling is Predictable, Empirically
Deep learning (DL) creates impactful advances following a virtuous recip...
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11/08/2017
Block-Sparse Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are used in state-of-the-art models in ...
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10/20/2017
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
We present Deep Voice 3, a fully-convolutional attention-based neural te...
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10/20/2017
Deep Voice 3: 2000-Speaker Neural Text-to-Speech
We present Deep Voice 3, a fully-convolutional attention-based neural te...
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10/10/2017
Mixed Precision Training
Deep neural networks have enabled progress in a wide variety of applicat...
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04/17/2017
Exploring Sparsity in Recurrent Neural Networks
Recurrent Neural Networks (RNN) are widely used to solve a variety of pr...
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07/15/2016
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Modern deep neural networks have a large number of parameters, making th...
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12/08/2015
