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20232026
most citedGlot500: Scaling Multilingual Corpora and Language Models to 500 Languages

17 citations · 19 across the 9 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CL2024

LangSAMP: Language-Script Aware Multilingual Pretraining

Yihong Liu, Haotian Ye, Chunlan Ma +2

Recent multilingual pretrained language models (mPLMs) often avoid using language embeddings -- learnable vectors assigned to individual languages. However, this places a significa…

cs.CL2024★ 1 cited

How Transliterations Improve Crosslingual Alignment

Yihong Liu, Mingyang Wang, Amir Hossein Kargaran +6

Recent studies have shown that post-aligning multilingual pretrained language models (mPLMs) using alignment objectives on both original and transliterated data can improve crossli…

cs.CL2024★ 1 cited

Exploring the Role of Transliteration in In-Context Learning for Low-resource Languages Written in Non-Latin Scripts

Chunlan Ma, Yihong Liu, Haotian Ye +1

Decoder-only large language models (LLMs) excel in high-resource languages across various tasks through few-shot or even zero-shot in-context learning (ICL). However, their perform…

cs.CL2024

TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data

Yihong Liu, Chunlan Ma, Haotian Ye +1

Transliterating related languages that use different scripts into a common script is effective for improving crosslingual transfer in downstream tasks. However, this methodology of…

cs.CL2024

TransliCo: A Contrastive Learning Framework to Address the Script Barrier in Multilingual Pretrained Language Models

Yihong Liu, Chunlan Ma, Haotian Ye +1

The world's more than 7000 languages are written in at least 293 scripts. Due to various reasons, many closely related languages use different scripts, which poses a difficulty for…

cs.CL2024

MoSECroT: Model Stitching with Static Word Embeddings for Crosslingual Zero-shot Transfer

Haotian Ye, Yihong Liu, Chunlan Ma +1

Transformer-based pre-trained language models (PLMs) have achieved remarkable performance in various natural language processing (NLP) tasks. However, pre-training such models can…