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Roger Waleffe

2 accepted papers

2026

Revisiting Efficiency–Accuracy Scaling in Mixture-of-Experts Architectures

ICML 2026poster

Mixture-of-Experts (MoEs) have become a central component of many state-of-the-art open-source and proprietary large language models. Despite their widespread adoption, it remains unclear how close existing MoE architectures are to optimal with respect to inference cost, as measured by accuracy per …

Cited by 0SourceScholar
2024

Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning

ICLR 2024poster

Methods for carefully selecting or generating a small set of training data to learn from, i.e., data pruning, coreset selection, and dataset distillation, have been shown to be effective in reducing the ever-increasing cost of training neural networks. Behind this success are rigorously designed, ye…