We think norms spread by imitation, but one deceptively simple rule tells a more human story

A paper appearing in Proceedings of the National Academy of Sciences offers a strikingly simple answer to a longstanding ...
IEEE

LLM-Augmented Multi-Fidelity Bayesian Optimization for Parameter Optimization in Human-Robot Collaborative Assembly

Abstract: Human-robot collaborative assembly (HRCA) is critical for manufacturing tasks like aircraft cabin drilling, where human contextual adaptability complements robotic repeatability. Parameter ...

Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

AI reasoning does not necessarily require spending huge amounts on frontier models. Instead, smaller models can yield ...
Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
IEEE

Adapting LLMs for High-Dimensional Bayesian Optimization

Abstract: Traditional Gaussian process surrogates fall short in coping with high-dimensional Bayesian optimization (HDBO) with irregular variables. We propose LoRA-VBLL, a novel framework that adapts ...