Abstract: Variable-rate coding is challenging but indispensable for learned image compression (LIC) that is in nature characterized by nonlinear transform coding (NTC). Existing methods for ...

Quantization plays a crucial role in deploying Large Language Models (LLMs) in resource-constrained environments. However, the presence of outlier features significantly hinders low-bit quantization.

Founders of quantum mechanics (QM) anticipated that revisions to classical physics due to strange elements of quantum reality, would necessitate similar changes in biology. Complexity theory, systems ...

Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...