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20222025
most citedSparse Periodic Systolic Dataflow for Lowering Latency and Power Dissipation of Convolutional Neural Network Accelerators

1 citations · 3 across the 4 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.CV2023★ 1 cited

CrAFT: Compression-Aware Fine-Tuning for Efficient Visual Task Adaptation

Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi +1

Transfer learning has become a popular task adaptation method in the era of foundation models. However, many foundation models require large storage and computing resources, which…

cs.CV2023★ 1 cited

Training-Free Acceleration of ViTs with Delayed Spatial Merging

Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi +1

Token merging has emerged as a new paradigm that can accelerate the inference of Vision Transformers (ViTs) without any retraining or fine-tuning. To push the frontier of training-…