research
∙
09/28/2022
FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation
Retrieval-augmented generation models offer many benefits over standalon...
share
research
∙
07/07/2022
Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling
This paper studies multi-task training of retrieval-augmented generation...
research
∙
03/16/2022
Transforming Sequence Tagging Into A Seq2Seq Task
Pretrained, large, generative language models (LMs) have had great succe...
research
∙
03/02/2021
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
The milestone improvements brought about by deep representation learning...
research
∙
10/23/2020
DICT-MLM: Improved Multilingual Pre-Training using Bilingual Dictionaries
Pre-trained multilingual language models such as mBERT have shown immens...
research
∙
10/07/2020
DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling
Pre-trained models like BERT (Devlin et al., 2018) have dominated NLP / ...
research
∙
07/24/2019
Sampled Softmax with Random Fourier Features
The computational cost of training with softmax cross entropy loss grows...
research
∙
10/29/2018
Distinct Sampling on Streaming Data with Near-Duplicates
In this paper we study how to perform distinct sampling in the streaming...
research
∙
10/16/2018
Stochastic Negative Mining for Learning with Large Output Spaces
We consider the problem of retrieving the most relevant labels for a giv...
research
∙
05/24/2018
A Practical Algorithm for Distributed Clustering and Outlier Detection
We study the classic k-means/median clustering, which are fundamental pr...
research
∙
05/23/2018
