activity
20182026
most citedNeural Network Controller for Autonomous Pile Loading Revised

2 citations · 3 across the 19 of their papers we have counts for

collaborators

20 papers

cs.LG2026

SUN: Reaching for Novelty in Reinforcement Learning

Wenyan Yang, Arsenii Mustafin, Dominik Baumann +2

Exploration in reinforcement learning (RL) remains a fundamental challenge. Recent goal-conditioned RL strategies (which select goals to encourage broader state coverage) have show…

cs.LG2026

DAGR: State-Conditioned Goal Representations via Difference-Aware Goal Cross-Attention

Xing Lei, Wenyan Yang, Xuetao Zhang +1

Goal-conditioned reinforcement learning hinges on how the goal is encoded. Contrastive, metric, temporal-distance, and information-theoretic encoders differ in objective. They stil…

cs.RO2026

ReGIL: Retrieval-Guided Imitation Learning from a Single Demonstration

Yuying Zhang, Francesco Verdoja, Wenyan Yang +1

Learning robot manipulation policies with deep neural networks from a single demonstration remains highly challenging, as even small deviations from the demonstrated trajectory can…

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.CV2026

PAWS: Perception of Articulation in the Wild at Scale from Egocentric Videos

Yihao Wang, Yang Miao, Wenshuai Zhao +8

Articulation perception aims to recover the motion and structure of articulated objects (e.g., drawers and cupboards), and is fundamental to 3D scene understanding in robotics, sim…