5 citations · 10 across the 10 of their papers we have counts for
5 papers · 1 filter
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors
Shuyue Stella Li, Beining Xu, Xiangyu Zhang +3
In this work, we study the features extracted by English self-supervised learning (SSL) models in cross-lingual contexts and propose a new metric to predict the quality of feature…
Narrowing the Gap between Zero- and Few-shot Machine Translation by Matching Styles
Weiting Tan, Haoran Xu, Lingfeng Shen +5
Large language models trained primarily in a monolingual setting have demonstrated their ability to generalize to machine translation using zero- and few-shot examples with in-cont…
Simple yet Effective Code-Switching Language Identification with Multitask Pre-Training and Transfer Learning
Shuyue Stella Li, Cihan Xiao, Tianjian Li +1
Code-switching, also called code-mixing, is the linguistics phenomenon where in casual settings, multilingual speakers mix words from different languages in one utterance. Due to i…
Condensing Multilingual Knowledge with Lightweight Language-Specific Modules
Haoran Xu, Weiting Tan, Shuyue Stella Li +4
Incorporating language-specific (LS) modules is a proven method to boost performance in multilingual machine translation. This approach bears similarity to Mixture-of-Experts (MoE)…
Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns
Shuyue Stella Li, Kenton Murray
In this work, we focus on intrasentential code-mixing and propose several different Synthetic Code-Mixing (SCM) data augmentation methods that outperform the baseline on downstream…