3 papers
cs.CL2026
FLEXITOKENS: Flexible Tokenization for Evolving Language Models
Abraham Toluwase Owodunni, Orevaoghene Ahia, Sachin Kumar
Adapting language models to new data distributions by simple finetuning is challenging. This is due to the rigidity of their subword tokenizers, which typically remain unchanged du…
cs.CL2026
A Comparative Empirical Study of Catastrophic Forgetting Mitigation in Sequential Task Adaptation for Continual Natural Language Processing Systems
Aram Abrahamyan, Sachin Kumar
Neural language models deployed in real-world applications must continually adapt to new tasks and domains without forgetting previously acquired knowledge. This work presents a co…
cs.CL2025
Continually Adding New Languages to Multilingual Language Models
Abraham Toluwase Owodunni, Sachin Kumar
Multilingual language models are trained on a fixed set of languages, and to support new languages, the models need to be retrained from scratch. This is an expensive endeavor and…