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GQA-{\mu}P: The maximal parameterization update for grouped query attention
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19 May
GQA-{\mu}P: The maximal parameterization update for grouped query attention
REPORT · WHAT · ArXiv CS.AI
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Other feeds and industry voices
19 May
GQLA: Group-Query Latent Attention for Hardware-Adaptive Large Language Model Decoding
arXiv:2605.15250v1 Announce Type: cross Abstract: Multi-head Latent Attention (MLA), the attention used in DeepSeek-V2/V3, jointly compresses keys and values into a low-rank
REPORT · WHAT · ArXiv CS.AIOPEN STORY
26 Mar
Scaling Attention via Feature Sparsity
arXiv:2603.22300v1 Announce Type: cross Abstract: Scaling Transformers to ultra-long contexts is bottlenecked by the $O(n^2 d)$ cost of self-attention. Existing methods reduce
REPORT · WHERE · ArXiv CS.AIOPEN STORY
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