KOSS: Improving Long-Term Sequence Modeling with Kalman Filtering

This research introduces a novel approach to long-term sequence modeling using Kalman filtering techniques. The potential impact lies in improved performance for applications requiring understanding and prediction of extended sequences, such as time series analysis and natural language processing.