Search Results for author:
Found 2 papers, 2 papers with code
FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark
While different learning schemes -- fine-tuning, zero-shot, and few-shot learning -- have been widely explored and compared for languages such as English, there is comparatively little work in Chinese to fairly and comprehensively evaluate and compare these methods and thus hinders cumulative progress.
A Generic Network Compression Framework for Sequential Recommender Systems
Current state-of-the-art sequential recommender models are typically based on a sandwich-structured deep neural network, where one or more middle (hidden) layers are placed between the input embedding layer and output softmax layer.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
