3 papers
cs.LG2026
Internalizing Outcome Supervision into Process Supervision: A New Paradigm for Reinforcement Learning for Reasoning
Fei Ding, Yongkang Zhang, Runhao Liu +4
The central challenge of reinforcement learning for reasoning lies not only in the sparsity of outcome-level supervision, but more fundamentally in how to transform feedback provid…
cs.LG2026
Rethinking the Comparison Unit in Sequence-Level Reinforcement Learning: An Equal-Length Paired Training Framework from Loss Correction to Sample Construction
Fei Ding, Yongkang Zhang, Runhao Liu +5
This paper investigates the length problem in sequence-level relative reinforcement learning. We observe that, although existing methods partially alleviate length-related phenomen…
cs.CV2026
PoseStreamer: A Multi-modal Framework for 3D Tracking of Unseen Moving Objects
Huiming Yang, Linglin Liao, Fei Ding +2
Six degree of freedom (6DoF) pose estimation for novel objects is a critical task in computer vision, yet it faces significant challenges in high-speed and low-light scenarios wher…