2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2023
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings
Daniel Rotem, Michael Hassid, Jonathan Mamou +1
Adaptive inference is a simple method for reducing inference costs. The method works by maintaining multiple classifiers of different capacities, and allocating resources to each t…
cs.CL2022★ 2 cited
How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers
Michael Hassid, Hao Peng, Daniel Rotem +4
The attention mechanism is considered the backbone of the widely-used Transformer architecture. It contextualizes the input by computing input-specific attention matrices. We find…