2 citations · 3 across the 3 of their papers we have counts for
3 papers
QLESS: A Quantized Approach for Data Valuation and Selection in Large Language Model Fine-Tuning
Moses Ananta, Muhammad Farid Adilazuarda, Zayd Muhammad Kawakibi Zuhri +2
Fine-tuning large language models (LLMs) is often constrained by the computational costs of processing massive datasets. We propose \textbf{QLESS} (Quantized Low-rank Gradient Simi…
IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Genta Indra Winata +2
Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixe…
The Obscure Limitation of Modular Multilingual Language Models
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Ayu Purwarianti
We expose the limitation of modular multilingual language models (MLMs) in multilingual inference scenarios with unknown languages. Existing evaluations of modular MLMs exclude the…