Search Results for author:
Found 6 papers, 3 papers with code
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models
In this paper, we start with a conceptual definition of AGI and briefly review how NLP solves a wide range of tasks via a chat system.
Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism
The Mixture of Experts (MoE) model becomes an important choice of large language models nowadays because of its scalability with sublinear computational complexity for training and inference.
Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast
In this paper, we present Pangu-Weather, a deep learning based system for fast and accurate global weather forecast.
Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
Neural architecture search (NAS) has attracted increasing attentions in both academia and industry.
GOLD-NAS: Gradual, One-Level, Differentiable
There has been a large literature of neural architecture search, but most existing work made use of heuristic rules that largely constrained the search flexibility.
Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters
Our approach bridges the gap from two aspects, namely, amending the estimation on the architectural gradients, and unifying the hyper-parameter settings in the search and re-training stages.
