BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop
Leshem Choshen Ryan Cotterell Mustafa Omer Gul Jaap Jumelet Tal Linzen Aaron Mueller Suchir Salhan Raj Sanjay Shah Alex Warstadt Ethan Gotlieb Wilcox
作者信息
Abstract
The goal of the BabyLM is to stimulate new research connections between cognitive modeling and language model pretraining. We invite contributions in this vein to the BabyLM Workshop, which will also include the 4th iteration of the BabyLM Challenge. As in previous years, the challenge features two ``standard'' tracks (Strict and Strict-Small), in which participants must train language models on under 100M or 10M words of data, respectively. This year, we move beyond our previous English-only pretraining datasets with a new Multilingual track, focusing on English, Dutch, and Chinese. For the workshop, we call for papers related to the overall theme of BabyLM, which includes training efficiency, small-scale training datasets, cognitive modeling, model evaluation, and architecture innovation.引用本文复制引用
Leshem Choshen,Ryan Cotterell,Mustafa Omer Gul,Jaap Jumelet,Tal Linzen,Aaron Mueller,Suchir Salhan,Raj Sanjay Shah,Alex Warstadt,Ethan Gotlieb Wilcox.BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop[EB/OL].(2026-02-24)[2026-02-27].https://arxiv.org/abs/2602.20092.学科分类
语言学/汉语/印欧语系
|国家预印本平台
评论