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 ...

Deep Learning-based embeddings are used widely for “dense retrieval” in information retrieval, computer vision, NLP, amongst others, owing to capture diverse types of semantic information. This ...

Abstract: Traditional XSS (Cross Site Scripting) scanners typically rely on attack vectors based on expert knowledge and manual testing, which not only incur high costs and long processing times but ...

Abstract: In this article, we present an efficient unified algorithm for the minimum Euclidean distance between two collections of compact convex sets, each of which can be a collection of convex ...