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cs.LG2026
Lifelong In-Context Learning with Transformers Requires Parametric Forms of Attention
Luke McDermott, Robert W. Heath, Rahul Parhi
Lifelong continual learning remains an obstacle on the path to human-like intelligence. Modern transformers show sparks of intelligence with in-context learning. The quadratic natu…
cs.LG2025
Finding Stable Subnetworks at Initialization with Dataset Distillation
Luke McDermott, Rahul Parhi
Recent works have shown that Dataset Distillation, the process for summarizing the training data, can be leveraged to accelerate the training of deep learning models. However, its…
cs.LG2025
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis
Akash Kumar, Rahul Parhi, Mikhail Belkin
Recent works have characterized the function-space inductive bias of infinite-width bounded-norm single-hidden-layer neural networks as a kind of bounded-variation-type space. This…