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cs.LG2024
MoRe Fine-Tuning with 10x Fewer Parameters
Wenxuan Tan, Nicholas Roberts, Tzu-Heng Huang +5
Parameter-efficient fine-tuning (PEFT) techniques have unlocked the potential to cheaply and easily specialize large pretrained models. However, the most prominent approaches, like…
cs.LG2024
Pretrained Hybrids with MAD Skills
Nicholas Roberts, Samuel Guo, Zhiqi Gao +5
While Transformers underpin modern large language models (LMs), there is a growing list of alternative architectures with new capabilities, promises, and tradeoffs. This makes choo…