7 citations · 17 across the 7 of their papers we have counts for
9 papers
VLRLA: Deployment-Time Adaptation of Vision-Language-Action Models through In-Context Reinforcement Learning
Diyuan Shi, Yiqi Tang, Hongyin Zhang +2
Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-conditioned manipulation. Howeve…
PreferenceFlow: Test-Time Guidance of Flow-Matching Robot Policies from Human Interventions
Yiqi Tang, Diyuan Shi, Runze Li +1
Flow-matching policies can represent complex robot behaviors but remain susceptible to local errors under distribution shift at deployment. Many reinforcement learning approaches t…
World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems
Runze Li, Hongyin Zhang, Junxi Jin +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action. However, most existing approa…
NFPO: Stabilized Policy Optimization of Normalizing Flow for Robotic Policy Learning
Diyuan Shi, Yiqi Tang, Zifeng Zhuang +1
Deep Reinforcement Learning (DRL) has experienced significant advancements in recent years and has been widely used in many fields. In DRL-based robotic policy learning, however, c…
Variational empirical Bayes variable selection in high-dimensional logistic regression
Yiqi Tang, Ryan Martin
Logistic regression involving high-dimensional covariates is a practically important problem. Often the goal is variable selection, i.e., determining which few of the many covariat…
Empirical Bayes inference in sparse high-dimensional generalized linear models
Yiqi Tang, Ryan Martin
High-dimensional linear models have been widely studied, but the developments in high-dimensional generalized linear models, or GLMs, have been slower. In this paper, we propose an…
An Imitation Game for Learning Semantic Parsers from User Interaction
Ziyu Yao, Yiqi Tang, Wen-tau Yih +2
Despite the widely successful applications, bootstrapping and fine-tuning semantic parsers are still a tedious process with challenges such as costly data annotation and privacy ri…
Empirical priors for prediction in sparse high-dimensional linear regression
Ryan Martin, Yiqi Tang
In this paper we adopt the familiar sparse, high-dimensional linear regression model and focus on the important but often overlooked task of prediction. In particular, we consider…
Label Propagation on K-partite Graphs with Heterophily
Dingxiong Deng, Fan Bai, Yiqi Tang +3
In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption. Homophily label propagation (i.e., two connected nodes share sim…