Research
NLP
Bag of Tricks for Efficient Text Classification
April 3, 2017
Abstract
This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of accuracy, and many orders of magnitude faster for training and evaluation. We can train fastText on more than one billion words in less than ten minutes using a standard multicore CPU, and classify half a million sentences among 312K classes in less than a minute.
Related Publications
November 16, 2022
NLP
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models
Kushal Tirumala, Aram H. Markosyan, Armen Aghajanyan, Luke Zettlemoyer
November 16, 2022
October 31, 2022
NLP
Autoregressive Search Engines: Generating Substrings as Document Identifiers
Fabio Petroni, Giuseppe Ottaviano, Michele Bevilacqua, Patrick Lewis, Scott Yih, Sebastian Riedel
October 31, 2022
December 06, 2020
NLP
Pre-training via Paraphrasing
Michael Lewis, Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer, Marjan Ghazvininejad, Sida Wang
December 06, 2020
November 30, 2020
NLP
Where Are You? Localization from Embodied Dialog
Dhruv Batra, Devi Parikh, Meera Hahn, Jacob Krantz, James Rehg, Peter Anderson, Stefan Lee
November 30, 2020
April 30, 2018
NLP
Speech & Audio
Identifying Analogies Across Domains | Facebook AI Research
Yedid Hoshen, Lior Wolf
April 30, 2018
November 01, 2018
NLP
Computer Vision
Non-Adversarial Unsupervised Word Translation | Facebook AI Research
Yedid Hoshen, Lior Wolf
November 01, 2018
December 02, 2018
NLP
Computer Vision
One-Shot Unsupervised Cross Domain Translation | Facebook AI Research
Sagie Benaim, Lior Wolf
December 02, 2018
June 30, 2019
NLP
Variational Training for Large-Scale Noisy-OR Bayesian Networks | Facebook AI Research
Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth
June 30, 2019
Help Us Pioneer The Future of AI
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
Product experiences
Foundational models
Product experiences
Latest news
Foundational models
Meta © 2024