6 citations · 15 across the 11 of their papers we have counts for
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cs.LG2023★ 3 cited
On the Long Range Abilities of Transformers
Itamar Zimerman, Lior Wolf
Despite their dominance in modern DL and, especially, NLP domains, transformer architectures exhibit sub-optimal performance on long-range tasks compared to recent layers that are…
cs.LG2023★ 6 cited
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption
Itamar Zimerman, Moran Baruch, Nir Drucker +3
Designing privacy-preserving deep learning models is a major challenge within the deep learning community. Homomorphic Encryption (HE) has emerged as one of the most promising appr…