12 citations · 30 across the 9 of their papers we have counts for
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cs.LG2022
Faith: An Efficient Framework for Transformer Verification on GPUs
Boyuan Feng, Tianqi Tang, Yuke Wang +5
Transformer verification draws increasing attention in machine learning research and industry. It formally verifies the robustness of transformers against adversarial attacks such…
cs.LG2022★ 2 cited
Dynamic N:M Fine-grained Structured Sparse Attention Mechanism
Zhaodong Chen, Yuying Quan, Zheng Qu +3
Transformers are becoming the mainstream solutions for various tasks like NLP and Computer vision. Despite their success, the high complexity of the attention mechanism hinders the…
cs.LG2021★ 12 cited
Transformer Acceleration with Dynamic Sparse Attention
Liu Liu, Zheng Qu, Zhaodong Chen +2
Transformers are the mainstream of NLP applications and are becoming increasingly popular in other domains such as Computer Vision. Despite the improvements in model quality, the e…