How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases

31 May 2023

Papers citing "How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases"

6 / 6 papers shown

Title
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora Alex Warstadt Aaron Mueller Leshem Choshen E. Wilcox Chengxu Zhuang ... Rafael Mosquera Bhargavi Paranjape Adina Williams Tal Linzen Ryan Cotterell 38 107 0 10 Apr 2025
BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency Akari Haga Akiyo Fukatsu Miyu Oba Arianna Bisazza Yohei Oseki 35 1 0 14 Nov 2024
Filtered Corpus Training (FiCT) Shows that Language Models can Generalize from Indirect Evidence Abhinav Patil Jaap Jumelet Yu Ying Chiu Andy Lapastora Peter Shen Lexie Wang Clevis Willrich Shane Steinert-Threlkeld 27 13 0 24 May 2024
Transformers Generalize Linearly Jackson Petty Robert Frank AI4CE 213 16 0 24 Sep 2021
Frequency Effects on Syntactic Rule Learning in Transformers Jason W. Wei Dan Garrette Tal Linzen Ellie Pavlick 82 62 0 14 Sep 2021
How Can We Accelerate Progress Towards Human-like Linguistic Generalization? Tal Linzen 218 188 0 03 May 2020