461 citations · 1.1k across the 22 of their papers we have counts for
25 papers
PRISM: Evaluating POSIX Storage Systems for AI Research Workflows
Adithya Kumar, Aditya Basu, Abhinandan Prativadi +4
Large GPU clusters for AI research rely on POSIX-based storage spanning code authoring, data preparation, and model checkpointing. The metric that matters is researcher iteration s…
Code World Model Preparedness Report
Daniel Song, Peter Ney, Cristina Menghini +21
This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conducted pre-release testing across…
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48
We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can…
Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
Jared Fernandez, Luca Wehrstedt, Leonid Shamis +5
Dramatic increases in the capabilities of neural network models in recent years are driven by scaling model size, training data, and corresponding computational resources. To devel…
Altogether: Image Captioning via Re-aligning Alt-text
Hu Xu, Po-Yao Huang, Xiaoqing Ellen Tan +10
This paper focuses on creating synthetic data to improve the quality of image captions. Existing works typically have two shortcomings. First, they caption images from scratch, ign…
Characterizing and Efficiently Accelerating Multimodal Generation Model Inference
Yejin Lee, Anna Sun, Basil Hosmer +27
Generative artificial intelligence (AI) technology is revolutionizing the computing industry. Not only its applications have broadened to various sectors but also poses new system…