Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...

We describe a concrete device roadmap towards a fault-tolerant quantum computing architecture based on noise-resilient, topologically protected Majorana-based qubits. Our roadmap encompasses four ...

This repository features Data Structures and Algorithms (DSA) practices in Dart, focusing on mastering fundamental programming concepts and problem-solving techniques.

Abstract: Code representation learning is an important way to encode the semantics of source code through pre-training. The learned representation supports a variety of downstream tasks, such as ...

Abstract: This letter introduces a new refined optimization strategy to achieve the pencil/shaped beam pattern synthesis of uniform amplitude rotated linear aperiodic array including the mutual ...