2 citations · 2 across the 5 of their papers we have counts for
6 papers
Online Language Adaptive Sampling for Better Distributed Cross-lingual Gains
Quang Phuoc Nguyen, Félix Gaschi, David Anugraha +2
Realignment is a promising approach for improving the cross-lingual transfer ability of multilingual language models, particularly for extremely low-resource languages (LRLs). Howe…
Can Large Language Models Understand, Reason About, and Generate Code-Switched Text?
Genta Indra Winata, David Anugraha, Patrick Amadeus Irawan +15
Code-switching is a pervasive phenomenon in multilingual communication, yet the robustness of large language models (LLMs) in mixed-language settings remains insufficiently underst…
Rethinking what Matters: Effective and Robust Multilingual Realignment for Low-Resource Languages
Quang Phuoc Nguyen, David Anugraha, Felix Gaschi +2
Realignment is a promising strategy to improve cross-lingual transfer in multilingual language models. However, empirical results are mixed and often unreliable, particularly for t…
AlignFreeze: Navigating the Impact of Realignment on the Layers of Multilingual Models Across Diverse Languages
Steve Bakos, Félix Gaschi, David Guzmán +3
Realignment techniques are often employed to enhance cross-lingual transfer in multilingual language models, still, they can sometimes degrade performance in languages that differ…
Multilingual Clinical NER: Translation or Cross-lingual Transfer?
Xavier Fontaine, Félix Gaschi, Parisa Rastin +1
Natural language tasks like Named Entity Recognition (NER) in the clinical domain on non-English texts can be very time-consuming and expensive due to the lack of annotated data. C…
Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers
Félix Gaschi, Patricio Cerda, Parisa Rastin +1
Without any explicit cross-lingual training data, multilingual language models can achieve cross-lingual transfer. One common way to improve this transfer is to perform realignment…