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cs.LG2026
Beware of the Batch Size: Hyperparameter Bias in Evaluating LoRA
Sangyoon Lee, Jaeho Lee
Low-rank adaptation (LoRA) is a standard approach for fine-tuning large language models, yet its many variants report conflicting empirical gains, often on the same benchmarks. We…
cs.LG2026
Fast Training of Sinusoidal Neural Fields via Scaling Initialization
Taesun Yeom, Sangyoon Lee, Jaeho Lee
Neural fields are an emerging paradigm that represent data as continuous functions parameterized by neural networks. Despite many advantages, neural fields often have a high traini…
cs.LG2024
In Search of a Data Transformation That Accelerates Neural Field Training
Junwon Seo, Sangyoon Lee, Kwang In Kim +1
Neural field is an emerging paradigm in data representation that trains a neural network to approximate the given signal. A key obstacle that prevents its widespread adoption is th…