arxiv
PublishedApril 3, 2026 at 4:00 AM
▲bullish
QUEST: A robust attention formulation using query-modulated spherical attention
Publisher summary· verbatim
arXiv:2604.00199v1 Announce Type: cross Abstract: The Transformer model architecture has become one of the most widely used in deep learning and the attention mechanism is at its core. The standard attention formulation uses a softmax operation applied to a scaled dot product between query and key v
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems10harxivQuery-Driven Learning for Lifted Reasoning10harxivThe Social World Model Evaluation Gap10harxivConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models10hThe Bubble Brief
MON · WED · FRIRead deep-learning insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗