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06/30/2023
Stitched ViTs are Flexible Vision Backbones
Large pretrained plain vision Transformers (ViTs) have been the workhors...
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03/26/2023
Illuminati: Towards Explaining Graph Neural Networks for Cybersecurity Analysis
Graph neural networks (GNNs) have been utilized to create multi-layer gr...
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02/02/2023
A Survey on Efficient Training of Transformers
Recent advances in Transformers have come with a huge requirement on com...
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12/05/2022
MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learning
The deep learning community has witnessed an exponentially growing inter...
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09/19/2022
EcoFormer: Energy-Saving Attention with Linear Complexity
Transformer is a transformative framework that models sequential data an...
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11/22/2021
Mesa: A Memory-saving Training Framework for Transformers
There has been an explosion of interest in designing high-performance Tr...
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09/23/2021
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
We aim to identify how different components in the KD pipeline affect th...
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05/29/2021
Less is More: Pay Less Attention in Vision Transformers
Transformers have become one of the dominant architectures in deep learn...
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05/04/2021
End-to-end One-shot Human Parsing
Previous human parsing models are limited to parsing humans into pre-def...
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03/19/2021
Scalable Visual Transformers with Hierarchical Pooling
The recently proposed Visual image Transformers (ViT) with pure attentio...
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12/22/2020
Progressive One-shot Human Parsing
Prior human parsing models are limited to parsing humans into classes pr...
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11/27/2019