Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

David Ussery discusses using Machine Learning methods to predict the pathogenicity of a bacterial infection based on genome ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

RUBICON estimates conversation quality for domain-specific assistants by learning rubrics for Satisfaction (SAT) and Dissatisfaction (DSAT) from labeled conversations. It involves three steps: ...

Explore the transformative technique of RAFT, a synergy of retrieval-augmented generation and fine-tuning for domain-specific language model proficiency, tailored for precision in open-book question ...

Microsoft Research introduces AdaptLLM, a new method for training large language models (LLMs) to perform specialized tasks more effectively.

Traditional machine learning (ML) models have paved the way for groundbreaking advancements, but a new paradigm is emerging: domain-specific LLMs.

The design automation community has been actively exploring machine learning (ML) for very-large-scale-integrated (VLSI) computer-aided design (CAD). Many studies have explored learning-based ...