4 papers
Shared LoRA Subspaces for almost Strict Continual Learning
Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +2
Adapting large pretrained models to new tasks efficiently and continually is crucial for real-world deployment but remains challenging due to catastrophic forgetting and the high c…
EigenLoRAx: Recycling Adapters to Find Principal Subspaces for Resource-Efficient Adaptation and Inference
Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +1
The rapid growth of large models has raised concerns about their environmental impact and equity in accessibility due to significant computational costs. Low-Rank Adapters (LoRA) o…
Name That Part: 3D Part Segmentation and Naming
Soumava Paul, Prakhar Kaushik, Ankit Vaidya +2
We address semantic 3D part segmentation: decomposing objects into parts with meaningful names. While datasets exist with part annotations, their definitions are inconsistent acros…
The Universal Weight Subspace Hypothesis
Prakhar Kaushik, Shravan Chaudhari, Ankit Vaidya +2
We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence…