Researchers from UCLA and Meta AI have introduced d1, a novel framework using reinforcement learning (RL) to significantly enhance the reasoning capabilities of diffusion-based large language models ...

The move echoes efforts by the administration to find financial upsides for its foreign-policy moves in places like Ukraine and Gaza, and follows a multiweek bombing campaign by the U.S. aimed at ...

This research proposes a novel framework that integrates Large Language Models (LLMs) with Proximal Policy Optimization (PPO), a reinforcement learning technique, to improve stock price predictions ...

This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method ...

250305.019.W8 in the next few weeks, staggered by device and carrier. Google says its enhanced step count algorithm was leading to "higher than expected" step counts, and is "reverting" to the ...

We propose an ISSE-driven proximal policy optimization (ISSE-PPO) algorithm to jointly optimize the compression ratio (CR), channel assignment, and power allocation in WSIT systems under the ...

This repository contains code and resources for research on using reinforcement learning, particularly the Post-Decision Proximal Policy Optimization (PDPPO), for the Stochastic Discrete Lot-Sizing ...