IEEE

Dynamic Optimization of Transportation Networks Using Big Data-Driven Reinforcement Learning

Abstract: The dynamic optimization of large-scale transportation networks presents significant challenges due to their complexity, stochasticity, and the need for real-time decision-making. In ...
IEEE

Graph-Based Dual-Agent Deep Reinforcement Learning for Dynamic Human–Machine Hybrid Reconfiguration Manufacturing Scheduling

Abstract: Human–machine hybrid reconfiguration manufacturing is an emerging paradigm in the field of precision equipment production and can greatly improve the production capability of the workshop.
GitHub

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. Feburary 9, 2026: 🔥 We released a free interactive demo ...
GitHub

learnalign_data_selection_for_llm_reinforcement_learning_with_improved_gradient_.md

To address data selection for RLVR post-training, LearnAlign is proposed—utilizing "gradient alignment" as a representativeness metric and "success rate $V(\xi)=p(1 ...