3 papers
cs.LG2026
TailLoR: Protecting Principal Components in Parameter-Efficient Continual Learning
Marius Dragoi, Ioana Pintilie, Alexandra Dragomir +2
Parameter-efficient finetuning methods based on spectral decomposition have enabled progress in Continual Learning. In this paper we introduce TailLoR, which utilizes the singular…
cs.LG2026
JumpLoRA: Sparse Adapters for Continual Learning in Large Language Models
Alexandra Dragomir, Ioana Pintilie, Antonio Barbalau +6
Adapter-based methods have become a cost-effective approach to continual learning (CL) for Large Language Models (LLMs), by sequentially learning a low-rank update matrix for each…
cs.CL2026
CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning
Alexandra Dragomir, Florin Brad, Radu Tudor Ionescu
Large language models (LLMs) have demonstrated competitive performance in zero-shot multilingual machine translation (MT). Some follow-up works further improved MT performance via…