This reinforcement learning system provides token-level implicit process rewards, calculated through a log-ratio formulation between a learned reward model and a reference model. Rather than manual ...

Methods: Thirty-two participants, equally divided between the explicit and implicit learning groups, participated in a throwing task. The explicit learning group began at a significant distance from ...

Training LLMs and VLMs through reinforcement learning delivers better results than using hand-crafted examples.

This method could, in theory, lead to an unobserved covariate ... On the other hand, participants whose learning was only implicit had an opposite pattern: they were better in learning regularities of ...

The basis of social learning theory is simple: People learn by watching other people. We can learn from anyone—teachers, parents, siblings, peers, co-workers, YouTube influencers, athletes ...

More than 3,000 pages of documents reveal how years of betrayals led to a messy court battle that threatens the future of ...

Nevertheless, existing federated learning recommender systems have been shown to pose potential threats during both the model training and inference phases ... Furthermore, AFedDFM effectively learns ...

Artificial intelligence (AI) is fundamentally changing how we interact with technology, increasing productivity and expanding capabilities. As this transformation unfolds, it presents both ...

Firstly, we propose a method to extract implicit label information from the feature space to replenish the binary label information. Secondly, we learn the positive correlation between features to ...

Welcome to the Power Apps update! See what’s new in Power Apps. A summary of product, community, and learning updates from throughout Jan. The Microsoft Power CAT team is excited to announce a series ...