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Found 4 papers, 0 papers with code
Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
In this study, we conduct a comparative analysis of INT and FP quantization with the same bit-width, revealing that the optimal quantization format varies across different layers due to the complexity and diversity of tensor distribution.
Cloud-Device Collaborative Adaptation to Continual Changing Environments in the Real-world
To enable the device model to deal with changing environments, we propose a new learning paradigm of Cloud-Device Collaborative Continual Adaptation, which encourages collaboration between cloud and device and improves the generalization of the device model.
Analysis of Quantization on MLP-based Vision Models
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-bit integers.
Panoramic Image Reflection Removal
This paper studies the problem of panoramic image reflection removal, aiming at reliving the content ambiguity between reflection and transmission scenes.
