A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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FreeNeRF introduces free frequency regularization to improve few-shot neural rendering by addressing frequency-related challenges in NeRF training.
Atindra Jha, Margaret Li, Jure Leskovec, et al.
Mixture-of-Experts models overfit more to repeated training data than dense models, with degradation increasing with sparsity; masking-based regularization can mitigate but not eliminate the gap.
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This paper investigates whether model editing harms the general abilities of large language models and proposes regularization as a mitigation strategy.
Chunming Li, Chenyang Xu, Changfeng Gui, et al.
Proposes a variational level set formulation with a distance regularization term that eliminates the need for reinitialization, enabling stable and efficient image segmentation.
Takeru Miyato, Shin‐ichi Maeda, Masanori Koyama, et al.
Virtual Adversarial Training (VAT) regularizes models by enforcing local smoothness of the label distribution via a computationally efficient, label-free adversarial direction, achieving state-of-the-art semi-supervised learning on SVHN and CIFAR-10.
Hui Zou, Trevor Hastie
The elastic net combines L1 and L2 penalties for regularization and variable selection, outperforming the lasso especially when p≫n and encouraging a grouping effect among correlated predictors.
Yueyi Liu, Chi Zhang, Sen Cui, et al.
ElasticTTT introduces a prior-preserving test-time tuning framework for video editing that prevents prior collapse via target distribution regularization, contrastive CFG, and asynchronous noise scheduling.