Search Results for author:
Found 3 papers, 0 papers with code
Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform
Through this gateway, users have the opportunity to submit their questions, testing the models on a personalized and potentially broader range of capabilities.
ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis
This paper introduces ConvTimeNet, a novel deep hierarchical fully convolutional network designed to serve as a general-purpose model for time series analysis.
Generative Pretrained Hierarchical Transformer for Time Series Forecasting
Secondly, the one-step generation schema is widely followed, which necessitates a customized forecasting head and overlooks the temporal dependencies in the output series, and also leads to increased training costs under different horizon length settings.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
