Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
Journal of Medical Internet Research

How to Design, Create, and Evaluate an Instruction-Tuning Dataset for Large Language Model Training in Health Care: Tutorial From a Clinical Perspective

Moreover, we discuss strategies for metadata selection and human evaluation to ensure the quality and effectiveness of ITDs. By integrating these elements, this tutorial provides a structured ...
IEEE

Vechicle Routing Problem with Clover Clustering and Adaptive Large Neighborhood Algorithm

Abstract: Distribution cost is one of the major cost components and hence the opportunity for improvement in supply chain management of any company. The research introduces a pragmatic approach in ...