Author

Sahil Joshi

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#artificial intelligence Preprint Oct 2026

Stratified Sparse Attention: Reducing the Sparse-to-Dense Gap at Extreme Sparsity

Large Language Model inference over long contexts is increasingly bottlenecked by the cost of attending to a growing Key-Value (KV) cache. Sparse attention reduces this cost by accessing only a fraction of the cache, but existing methods face a trade-off between deterministic retrieval, which captures high-scoring toke...

Sahil Joshi, Prithvi Dixit, Aryan Katiyar et al. · 0 citations

#machine learning Preprint Feb 2026

SOCKET: SOft Collision Kernel EsTimator for Sparse Attention

This work revisits Locality-Sensitive Hashing (LSH) and introduces SOCKET, a SOft Collision Kernel EsTimator that replaces hard bucket matches with probabilistic, similarity-aware aggregation, and reframes LSH from a candidate-generation mechanism into a principled scoring kernel for sparse attention.

Sahil Joshi, Agniva Chowdhury, W. Bellinger et al. · 3 citations