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cs.LG2026

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions

Jeff A. Bilmes, Gantavya Bhatt, Arnav M. Das

Neural scaling laws appraise data through dataset size, while the Vendi Score uses quantum entropy to measure dataset value. We show both that common neural-scaling-law objectives…

cs.LG2025

Tilted Sharpness-Aware Minimization

Tian Li, Tianyi Zhou, Jeffrey A. Bilmes

Sharpness-Aware Minimization (SAM) has been demonstrated to improve the generalization performance of overparameterized models by seeking flat minima on the loss landscape through…

cs.LG2025

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation

Arnav M. Das, Gantavya Bhatt, Lilly Kumari +2

Retrieval augmentation, the practice of retrieving additional data from large auxiliary pools, has emerged as an effective technique for enhancing model performance in the low-data…

cs.LG2025

Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective

Sahil Verma, Gantavya Bhatt, Avi Schwarzschild +6

Despite the advanced capabilities of contemporary machine learning (ML) models, they remain vulnerable to adversarial and backdoor attacks. This vulnerability is particularly conce…

cs.LG2024

Deep Submodular Peripteral Networks

Gantavya Bhatt, Arnav Das, Jeff Bilmes

Submodular functions, crucial for various applications, often lack practical learning methods for their acquisition. Seemingly unrelated, learning a scaling from oracles offering g…