KOSS: Improving Long-Term Sequence Modeling with Kalman Filtering
Published:Dec 18, 2025 16:25
•1 min read
•ArXiv
Analysis
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.
Key Takeaways
Reference
“The paper focuses on Kalman-Optimal Selective State Spaces for Long-Term Sequence Modeling.”