5 papers
When English Isn't the Best Teacher: Source Language Effects in Cross-Lingual In-Context Learning
Fred Philippy, Siwen Guo, Jacques Klein +1
Cross-lingual transfer in multilingual NLP has been widely explored in supervised fine-tuning contexts, where factors like data availability and linguistic similarity largely deter…
Why Low-Resource NLP Needs More Than Cross-Lingual Transfer: Lessons Learned from Luxembourgish
Fred Philippy, Siwen Guo, Jacques Klein +1
Cross-lingual transfer has become a central paradigm for extending natural language processing (NLP) technologies to low-resource languages. By leveraging supervision from high-res…
LuxInstruct: A Cross-Lingual Instruction Tuning Dataset For Luxembourgish
Fred Philippy, Laura Bernardy, Siwen Guo +2
Instruction tuning has become a key technique for enhancing the performance of large language models, enabling them to better follow human prompts. However, low-resource languages…
Enhancing Small Language Models for Cross-Lingual Generalized Zero-Shot Classification with Soft Prompt Tuning
Fred Philippy, Siwen Guo, Cedric Lothritz +2
In NLP, Zero-Shot Classification (ZSC) has become essential for enabling models to classify text into categories unseen during training, particularly in low-resource languages and…
LuxEmbedder: A Cross-Lingual Approach to Enhanced Luxembourgish Sentence Embeddings
Fred Philippy, Siwen Guo, Jacques Klein +1
Sentence embedding models play a key role in various Natural Language Processing tasks, such as in Topic Modeling, Document Clustering and Recommendation Systems. However, these mo…