2 papers
cs.CL2026
More Value per Key: Asymmetric Sparse Attention for Faster LLM Decoding
Noam Elata, Itay Lamprecht, Mikey Shechter +3
Autoregressive generation in Large Language Models (LLMs) is constrained by the memory and computational demands of attention mechanisms. Sparse attention methods mitigate this cos…
cs.CV2025
Filter Like You Test: Data-Driven Data Filtering for CLIP Pretraining
Mikey Shechter, Yair Carmon
We introduce Filter Like You Test (FLYT), an algorithm for curating large-scale vision-language datasets that learns the usefulness of each data point as a pretraining example. FLY…