Sebastian Borgeaud | DeepAI

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∙ 02/02/2023

Accelerating Large Language Model Decoding with Speculative Sampling

We present speculative sampling, an algorithm for accelerating transform...

0 Charlie Chen, et al. ∙

∙ 04/29/2022

Flamingo: a Visual Language Model for Few-Shot Learning

Building models that can be rapidly adapted to numerous tasks using only...

7 Jean-Baptiste Alayrac, et al. ∙

∙ 03/29/2022

Training Compute-Optimal Large Language Models

We investigate the optimal model size and number of tokens for training ...

6 Jordan Hoffmann, et al. ∙

∙ 02/15/2022

General-purpose, long-context autoregressive modeling with Perceiver AR

Real-world data is high-dimensional: a book, image, or musical performan...

2 Curtis Hawthorne, et al. ∙

∙ 02/02/2022

Unified Scaling Laws for Routed Language Models

The performance of a language model has been shown to be effectively mod...

2 Aidan Clark, et al. ∙

∙ 12/08/2021

Improving language models by retrieving from trillions of tokens

We enhance auto-regressive language models by conditioning on document c...

8 Sebastian Borgeaud, et al. ∙

∙ 07/30/2021

Perceiver IO: A General Architecture for Structured Inputs Outputs

The recently-proposed Perceiver model obtains good results on several do...

6 Andrew Jaegle, et al. ∙

∙ 11/28/2020

Human-Agent Cooperation in Bridge Bidding

We introduce a human-compatible reinforcement-learning approach to a coo...

0 Edward Lockhart, et al. ∙

∙ 08/26/2019

OpenSpiel: A Framework for Reinforcement Learning in Games

OpenSpiel is a collection of environments and algorithms for research in...

12 Marc Lanctot, et al. ∙

∙ 08/17/2019

Leveraging sentence similarity in natural language generation: Improving beam search using range voting

We propose a novel method for generating natural language sentences from...

0 Sebastian Borgeaud, et al. ∙

∙ 06/19/2019

Unsupervised Learning of Object Keypoints for Perception and Control

The study of object representations in computer vision has primarily foc...

0 Tejas Kulkarni, et al. ∙

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