Published on June 30, 2026, the post describes an architecture combining Full Attention and Linear Attention at the head level for long-context models.
Published on June 30, 2026, the post presents HydraHead, an architecture that combines Full Attention and Linear Attention separately for each head. According to the publication, the proposal is motivated by mechanistic interpretability and aims to support more efficient long-context models.
The text emphasizes that combining mechanisms at the head level offers a different degree of granularity, but reports no performance measurements or experimental details. To assess the claims, consult the original publication and check which methods, comparisons, and results it provides; do not extrapolate beyond what was reported.