18 citations · 44 across the 7 of their papers we have counts for
4 papers · 1 filter
ComputerSD: Online Self-Distillation from Real-Time Feedback for Computer-Use Agents
Yong Du, Tongbo Chen, Zhengxi Lu +5
Online training enables computer-use agents (CUAs) to improve through interaction with executable environments. However, existing methods primarily rely on sparse outcome rewards,…
Second-Moment Stochastic Approximation Methods
Tao Jiang, Lin Xiao
Classical stochastic approximation methods rely on estimators of the first moment (mean) of a random regression function. We study methods that employ estimators of both the first…
Dense Process Supervision for Search Agents via Fact Utility Estimation
Rongzhi Zhu, Xiangyu Liu, Yi Liu +7
Reinforcement learning (RL) for search agents typically relies on outcome rewards. However, it often fails to achieve effective credit assignment, due to the unclear value of inter…
CommerceVibe: Learning to Design E-Commerce Creatives as Executable Visual Code via Dual-Feedback Reinforcement Learning
Yajiao Xu, Jin Zhang, Jiangbo Ai +4
High-quality e-commerce creatives are essential for presenting products and conveying marketing messages. Recent diffusion models enable scalable creative generation and produce vi…