Litcius/Paper detail

Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, Ryan Cotterell

202368 citationsDOIOpen Access PDF

Abstract

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, Ryan Cotterell. Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning. 2023.

Topics & Concepts

AdinaComputer scienceSample (material)Artificial intelligenceNatural (archaeology)Natural language processingHistoryEngineeringArchaeologyPhysicsThermodynamicsFinite element methodStructural engineeringNatural Language Processing TechniquesTopic ModelingSpeech Recognition and Synthesis
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora | Litcius