Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds enterprise system prompt instructions into model weights, reducing inference ...

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...

2024 is going to be a huge year for the cross-section of generative AI/large foundational models and robotics. There’s a lot of excitement swirling around the potential for various applications, ...

FSU College of Engineering and Florida State University’s Resilient Infrastructure and Disaster Response Center examined several types of flood models to highlight their strengths and weaknesses and ...

Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know ...

NEW YORK, NY--(Marketwire - Sep 26, 2012) - Errors in financial models that banks use on a daily basis could lead to tremendous financial and non-financial losses. It is crucial for banks to ...

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...