research
∙
02/27/2023
LLaMA: Open and Efficient Foundation Language Models
We introduce LLaMA, a collection of foundation language models ranging f...
share
research
∙
07/08/2022
Improving Wikipedia Verifiability with AI
Verifiability is a core content policy of Wikipedia: claims that are lik...
research
∙
12/18/2021
The Web Is Your Oyster – Knowledge-Intensive NLP against a Very Large Web Corpus
In order to address the increasing demands of real-world applications, t...
research
∙
05/07/2021
ResMLP: Feedforward networks for image classification with data-efficient training
We present ResMLP, an architecture built entirely upon multi-layer perce...
research
∙
02/21/2020
Accessing Higher-level Representations in Sequential Transformers with Feedback Memory
Transformers are feedforward networks that can process input tokens in p...
research
∙
11/19/2019
End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
We study ResNet-, Time-Depth Separable ConvNets-, and Transformer-based ...
research
∙
11/01/2019
CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data
Pre-training text representations have led to significant improvements i...
research
∙
10/22/2019
Depth-Adaptive Transformer
State of the art sequence-to-sequence models perform a fixed number of c...
research
∙
07/02/2019
Augmenting Self-attention with Persistent Memory
Transformer networks have lead to important progress in language modelin...
research
∙
05/19/2019
Adaptive Attention Span in Transformers
We propose a novel self-attention mechanism that can learn its optimal a...
research
∙
03/28/2016
