activity
20222026
most citedOptimistic Multi-Agent Policy Gradient

1 citations · 3 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Internalizing Temporal Consistency in Video Object-Centric Learning without Explicit Regularization

Rongzhen Zhao, Zhiyuan Li, Juho Kannala +1

Video Object-Centric Learning (OCL) aims to represent objects as \textit{slot} vectors and maintain their consistency across frames. Slot-Slot Contrastive (SSC) loss has become the…

cs.CV2026

Cycle Consistency in Video Object-Centric Learning

Rongzhen Zhao, Zhiyuan Li, Ruonan Wei +2

Self-supervised video Object-Centric Learning (OCL) aims to discover distinct objects and associate them across time, whereas self-supervised Multi-Object Tracking (MOT) focuses on…

cs.CV2026

Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence

Zhiyuan Li, Rongzhen Zhao, Wenyan Yang +3

The de facto approach in video object-centric learning maintains temporal consistency through learned dynamics modules that predict future object representations, called slots. We…

cs.RO2026

Bridging the Embodiment Gap: Disentangled Cross-Embodiment Video Editing

Zhiyuan Li, Wenyan Yang, Wenshuai Zhao +4

Learning robotic manipulation from human videos is a promising solution to the data bottleneck in robotics, but the distribution shift between humans and robots remains a critical…

cs.LG2026

Sparsely Supervised Diffusion

Wenshuai Zhao, Zhiyuan Li, Yi Zhao +5

Diffusion models have shown remarkable success across a wide range of generative tasks. However, they often suffer from spatially inconsistent generation, arguably due to the inher…

cs.AI2025

Closed-Loop Vision-Language Planning for Multi-Agent Coordination

Zhiyuan Li, Wenshuai Zhao, Joni Pajarinen

Cooperative multi-agent reinforcement learning (MARL) struggles with sample efficiency, interpretability, and generalization. While Large Language Models (LLMs) offer powerful plan…