Are All Languages Equally Hard to Language-Model?

10 June 2018

Papers citing "Are All Languages Equally Hard to Language-Model?"

9 / 9 papers shown

Title
Evaluating Morphological Compositional Generalization in Large Language Models Mete Ismayilzada Yuan Chiang Jonne Sälevä Hale Sirin Abdullatif Köksal Bhuwan Dhingra Antoine Bosselut Lonneke van der Plas Duygu Ataman 50 4 0 16 Oct 2024
Machine Translation Models are Zero-Shot Detectors of Translation Direction Michelle Wastl Jannis Vamvas Rico Sennrich VLM 62 0 0 12 Jan 2024
Testing the Predictions of Surprisal Theory in 11 Languages Ethan Gotlieb Wilcox Tiago Pimentel Clara Meister Ryan Cotterell R. Levy LRM 75 66 0 07 Jul 2023
UniMorph 2.0: Universal Morphology Christo Kirov Ryan Cotterell John Sylak-Glassman Géraldine Walther Ekaterina Vylomova ... Arya D. McCarthy Sandra Kübler David Yarowsky Jason Eisner Mans Hulden 49 140 0 25 Oct 2018
Exploring the Syntactic Abilities of RNNs with Multi-task Learning Émile Enguehard Yoav Goldberg Tal Linzen 31 28 0 12 Jun 2017
Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling Kazuya Kawakami Chris Dyer Phil Blunsom KELM 36 34 0 23 Apr 2017
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies Tal Linzen Emmanuel Dupoux Yoav Goldberg 75 898 0 04 Nov 2016
Character-Level Language Modeling with Hierarchical Recurrent Neural Networks Kyuyeon Hwang Wonyong Sung 28 66 0 13 Sep 2016
Recurrent Neural Network Regularization Wojciech Zaremba Ilya Sutskever Oriol Vinyals ODL 102 2,768 0 08 Sep 2014