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Nilesh Prasad Pandey

2 accepted papers

2024

FouRA: Fourier Low-Rank Adaptation

NeurIPS 2024poster

While Low-Rank Adaptation (LoRA) has proven beneficial for efficiently fine-tuning large models, LoRA fine-tuned text-to-image diffusion models lack diversity in the generated images, as the model tends to copy data from the observed training samples. This effect becomes more pronounced at higher va…

Cited by 5SourcePDFScholar
2024

Sparse High Rank Adapters

NeurIPS 2024poster

Low Rank Adaptation (LoRA) has gained massive attention in the recent generative AI research. One of the main advantages of LoRA is its ability to be fused with pretrained models, adding no overhead during inference. However, from a mobile deployment standpoint, we can either avoid inference overhe…

Cited by 15SourcePDFScholar