23 citations · 32 across the 11 of their papers we have counts for
4 papers · 1 filter
Newton Matching for Generative Modeling: A Unified Framework for Fine-Tuning and Sampling
Zeyang Li, Yunan Wang, Paolo Giaretta +1
We develop Newton Matching, a unified framework for fine-tuning and sampling in generative modeling. The target is , where is the reward, the inverse tem…
DiRecT: Safe Diffusion-Based Planning via Receding-Horizon Denoising
Paolo Giaretta, Zeyang Li, Navid Azizan
Diffusion models have emerged as powerful tools for planning and control by learning multimodal distributions over actions and trajectories. Yet reliable inference-time safety enfo…
From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning
Ranxu zhang, zeyang li, Jiacheng Huang +5
Agentic reinforcement learning (Agentic RL) has achieved strong progress in tasks with clear success signals. However, many real-world agent applications require user-conditioned b…
Reachability-Augmented Dual Dynamic Programming for Optimal Path Parameterization
Yunan Wang, Jizhou Yan, Chuxiong Hu +1
Optimal path parameterization (OPP) is a fundamental problem for planning trajectories along a prescribed geometric path under kinodynamic constraints and task-dependent objectives…