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cs.LG2025
Bias-Restrained Prefix Representation Finetuning for Mathematical Reasoning
Sirui Liang, Pengfei Cao, Jian Zhao +3
Parameter-Efficient finetuning (PEFT) enhances model performance on downstream tasks by updating a minimal subset of parameters. Representation finetuning (ReFT) methods further im…
cs.LG2025
DATA: Decomposed Attention-based Task Adaptation for Rehearsal-Free Continual Learning
Huanxuan Liao, Shizhu He, Yupu Hao +2
Continual learning (CL) is essential for Large Language Models (LLMs) to adapt to evolving real-world demands, yet they are susceptible to catastrophic forgetting (CF). While tradi…