1 citations · 1 across the 6 of their papers we have counts for
6 papers
Enhancing Cross-Lingual Transfer through Reversible Transliteration: A Huffman-Based Approach for Low-Resource Languages
Wenhao Zhuang, Yuan Sun, Xiaobing Zhao
As large language models (LLMs) are trained on increasingly diverse and extensive multilingual corpora, they demonstrate cross-lingual transfer capabilities. However, these capabil…
CUTE: A Multilingual Dataset for Enhancing Cross-Lingual Knowledge Transfer in Low-Resource Languages
Wenhao Zhuang, Yuan Sun
Large Language Models (LLMs) demonstrate exceptional zero-shot capabilities in various NLP tasks, significantly enhancing user experience and efficiency. However, this advantage is…
TSCheater: Generating High-Quality Tibetan Adversarial Texts via Visual Similarity
Xi Cao, Quzong Gesang, Yuan Sun +2
Language models based on deep neural networks are vulnerable to textual adversarial attacks. While rich-resource languages like English are receiving focused attention, Tibetan, a…
EasyJudge: an Easy-to-use Tool for Comprehensive Response Evaluation of LLMs
Yijie Li, Yuan Sun
Recently, there has been a growing trend of employing large language models (LLMs) to judge the quality of other LLMs. Many studies have adopted closed-source models, mainly using…
MiLMo:Minority Multilingual Pre-trained Language Model
Junjie Deng, Hanru Shi, Xinhe Yu +3
Pre-trained language models are trained on large-scale unsupervised data, and they can fine-turn the model only on small-scale labeled datasets, and achieve good results. Multiling…
TiBERT: Tibetan Pre-trained Language Model
Yuan Sun, Sisi Liu, Junjie Deng +1
The pre-trained language model is trained on large-scale unlabeled text and can achieve state-of-the-art results in many different downstream tasks. However, the current pre-traine…