New study probes how axial attention works in time series foundation models
A new arXiv paper examines axial attention mechanisms increasingly used in Time Series Foundation Models, analyzing them through single location regression to explain their empirical success theoretically.
Read the full story at arXiv stat.ML ↗
Timeline · 1 report
- 2026-10-30 04:00 · arXiv stat.ML
Understanding axial attention in TSFMs through single location regression