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 ...

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, ...

Google researchers have proposed TurboQuant, a method for compressing the key-value caches that large language models rely on ...

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

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 ...

Hydrological models represent water movement in natural systems, and they are important for water resource planning and ...

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...