3 papers
cs.LG2025
TorchAO: PyTorch-Native Training-to-Serving Model Optimization
Andrew Or, Apurva Jain, Daniel Vega-Myhre +10
We present TorchAO, a PyTorch-native model optimization framework leveraging quantization and sparsity to provide an end-to-end, training-to-serving workflow for AI models. TorchAO…
cs.LG2025
Accelerating Transformer Inference and Training with 2:4 Activation Sparsity
Daniel Haziza, Timothy Chou, Dhruv Choudhary +7
In this paper, we demonstrate how to leverage 2:4 sparsity, a popular hardware-accelerated GPU sparsity pattern, to activations to accelerate large language model training and infe…
cs.CL2025
NeurIPS 2023 LLM Efficiency Fine-tuning Competition
Mark Saroufim, Yotam Perlitz, Leshem Choshen +11
Our analysis of the NeurIPS 2023 large language model (LLM) fine-tuning competition revealed the following trend: top-performing models exhibit significant overfitting on benchmark…