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Activation Quantization of Vision Encoders Needs Prefixing Registers
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Towards Understanding Best Practices for Quantization of Vision-Language Models
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Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
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Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
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Early-Exit Deep Neural Network - A Comprehensive Survey
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RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
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APQ-ViT: Towards Accurate Post-Training Quantization for Vision Transformer
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FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
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PTQ4ViT
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Post-Training Quantization for Vision Transformer
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PACT: PARAMETERIZED CLIPPING ACTIVATION FOR QUANTIZED NEURAL NETWORKS
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Explaining NonLinear Classification Decisions with Deep Taylor Decomposition
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