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cs.CV2026

DocPO: Advancing Document Policy Optimization via Tailored Step-Aware Rewards

Yunhao Wang, Binghong Wu, Zhenyu Huang +4

Reinforcement learning (RL) for document parsing often relies on reference-based rewards rooted in edit distance (e.g., tree edit distance), yet it remains hard to optimize in the…

cs.CV2026

R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow

Zijie Wu, Lixin Xu, Puhua Jiang +3

Video-guided 3D animation holds immense potential for content creation, offering intuitive and precise control over dynamic assets. However, practical deployment faces a critical y…

cs.CV2026

Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation

Peiyang Liu, Ziqiang Cui, Xi Wang +2

Iterative Retrieval-Augmented Generation (iRAG) has emerged as a powerful paradigm for answering complex multi-hop questions by progressively retrieving and reasoning over external…

cs.CV2026

ReBaR: Reference-Based Reasoning for Robust Pose Estimation from Monocular Images

Yongkang Cheng, Mingjiang Liang, Jifeng Ning +3

R}easoning for Robust Human Pose and Shape Estimation), designed to estimate human body shape and pose from single-view images. ReBaR effectively addresses the challenges of occlus…

cs.CV2026

MARRS: Masked Autoregressive Unit-based Reaction Synthesis

Yabiao Wang, Shuo Wang, Jiangning Zhang +3

This work aims at a challenging task: human action-reaction synthesis, i.e., generating human reactions conditioned on the action sequence of another person. Currently, autoregress…