2 papers
cs.LG2026
SOCKET: SOft Collision Kernel EsTimator for Sparse Attention
Sahil Joshi, Agniva Chowdhury, Wyatt Bellinger +5
Exploiting sparsity during long-context inference is key to scaling large language models, as attention dominates the cost of autoregressive decoding. Sparse attention reduces this…
cs.LG2026
RACE Attention: A Strictly Linear-Time Attention Layer for Training on Outrageously Large Contexts
Sahil Joshi, Agniva Chowdhury, Amar Kanakamedala +3
Softmax Attention has a quadratic time complexity in sequence length, which becomes prohibitive to run at long contexts, even with highly optimized GPU kernels. For example, FlashA…