3 papers
cs.AI2026
Dynamic Multi-Byte Prediction With Hierarchical Language Models
Abraham Toluwase Owodunni, Chibuzor Okocha, Christan Grant +2
Byte-level hierarchical language models (LMs) have recently emerged as a robust alternative to their popular counterparts that use subword tokenization. However, generating one byt…
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…