3 papers
cs.RO2026
Where Should Action Generation Begin? A Learnable Source Prior for Generative Robot Policies
Meipo Dai, Qiyuan Zhuang, He-Yang Xu +4
Generative robot policies typically begin action generation from an observation-independent standard Gaussian distribution, leaving the choice of source distribution underexplored.…
cs.RO2026
RAAP: Retrieval-Augmented Affordance Prediction with Cross-Image Action Alignment
Qiyuan Zhuang, He-Yang Xu, Yijun Wang +3
Understanding object affordances is essential for enabling robots to perform purposeful and fine-grained interactions in diverse and unstructured environments. However, existing ap…
cs.LG2026
Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting
Yijun Wang, Qiyuan Zhuang, Larysa Marchanka +1
Real-world time series exhibit temporally structured uncertainty: volatility clusters in turbulent regimes, dissipates in stable periods, and shifts abruptly around structural brea…