This article discusses the limitations of traditional recurrent neural networks (RNNs) in handling sequential data and the challenges of deploying resource-intensive models like Transformers…
Browsing: Sequence Modeling
Orchid is a new sequence modeling architecture that integrates a data-dependent convolution mechanism to overcome the limitations of traditional attention-based models. It aims to…
This survey provides a comprehensive overview of recent works that leverage sequence models such as the Transformer to solve sequential decision-making tasks. It discusses…
This survey presents a comprehensive overview of recent works that utilize sequence models such as the Transformer to solve sequential decision-making tasks. It discusses…