This important study describes long-range serial dependence of performance on a visual texture discrimination training task that manipulated conditions to induce differing degrees of location transfer ...

Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing supervised systems while uncovering biological patterns that traditional ...

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...

Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for generating images from pure noise by using the physics of heat and motion ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

Small and dense but filled with vitally important neural fibers, the brainstem has been hard for brain imaging technologies to dissect. New software reliably and finely resolves eight distinct nerve ...

Abstract: Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised learning ...

With so much money flooding into AI startups, it’s a good time to be an AI researcher with an idea to test out. And if the idea is novel enough, it might be easier to get the resources you need as an ...