From Characters to Words: Hierarchical Pre-trained Language Model for
Open-vocabulary Language Understanding

From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding

23 May 2023

Kayhan Batmanghelich

Changrong Zhang

Papers citing "From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding"

8 / 8 papers shown

Title
A Practical Guide to Fine-tuning Language Models with Limited Data Márton Szép Daniel Rueckert Rüdiger von Eisenhart-Rothe Florian Hinterwimmer SyDa ALM 49 2 0 14 Nov 2024
Heidelberg-Boston @ SIGTYP 2024 Shared Task: Enhancing Low-Resource Language Analysis With Character-Aware Hierarchical Transformers Frederick Riemenschneider Kevin Krahn 29 2 0 30 May 2024
Knowledge of Pretrained Language Models on Surface Information of Tokens Tatsuya Hiraoka Naoaki Okazaki 32 1 0 15 Feb 2024
Learning Mutually Informed Representations for Characters and Subwords Yilin Wang Xinyi Hu Matthew R. Gormley 36 0 0 14 Nov 2023
Char2Subword: Extending the Subword Embedding Space Using Robust Character Compositionality Gustavo Aguilar Bryan McCann Tong Niu Nazneen Rajani N. Keskar Thamar Solorio 47 12 0 24 Oct 2020
CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters Hicham El Boukkouri Olivier Ferret Thomas Lavergne Hiroshi Noji Pierre Zweigenbaum Junichi Tsujii 77 156 0 20 Oct 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 269 31,267 0 16 Jan 2013