Bit Allocation

Bit allocation optimizes the distribution of bits across different components of data, aiming to maximize efficiency and quality within resource constraints. Current research focuses on developing adaptive and efficient bit allocation strategies for various applications, including deep neural networks (DNNs), large language models (LLMs), and video/image compression, often employing techniques like mixed-precision quantization, salience-driven methods, and reinforcement learning algorithms. These advancements are crucial for improving the performance and reducing the computational burden of resource-intensive applications, impacting fields such as AI, multimedia processing, and communication systems.