6.5k citations · 10.4k across the 118 of their papers we have counts for
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Multitask Vision-Language Prompt Tuning
Sheng Shen, Shijia Yang, Tianjun Zhang +4
Prompt Tuning, conditioning on task-specific learned prompt vectors, has emerged as a data-efficient and parameter-efficient method for adapting large pretrained vision-language mo…
CSQ: Growing Mixed-Precision Quantization Scheme with Bi-level Continuous Sparsification
Lirui Xiao, Huanrui Yang, Zhen Dong +3
Mixed-precision quantization has been widely applied on deep neural networks (DNNs) as it leads to significantly better efficiency-accuracy tradeoffs compared to uniform quantizati…
NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers
Yijiang Liu, Huanrui Yang, Zhen Dong +3
The complicated architecture and high training cost of vision transformers urge the exploration of post-training quantization. However, the heavy-tailed distribution of vision tran…
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
Jinhyung Park, Chenfeng Xu, Shijia Yang +4
While recent camera-only 3D detection methods leverage multiple timesteps, the limited history they use significantly hampers the extent to which temporal fusion can improve object…
Analysis of Quantization on MLP-based Vision Models
Lingran Zhao, Zhen Dong, Kurt Keutzer
Quantization is wildly taken as a model compression technique, which obtains efficient models by converting floating-point weights and activations in the neural network into lower-…
Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers
Kevin Miao, Akash Gokul, Raghav Singh +5
Recent trends in self-supervised representation learning have focused on removing inductive biases from training pipelines. However, inductive biases can be useful in settings when…