3 citations · 3 across the 19 of their papers we have counts for
22 papers
Retrieve in Time, Correct in Frequency
Yuze Fan, Yue Cao, Pengjie Gao +7
Frozen vision-language-action (VLA) policies generate temporally extended action chunks, but long-horizon manipulation remains vulnerable to accumulated execution error and visual…
HERA: Historical Evidence Routing Adapter for Physical Prediction in Latent World Models
Yuanruyi, Yue Cao, Haojia Gao +7
Predictive video models have emerged as promising world models by learning latent visual dynamics from large-scale video. Yet these models remain challenged by physical events unde…
FlowPRO: Reward-Free Reinforced Fine-Tuning of Flow-Matching VLAs via Proximalized Preference Optimization
Yihao Wu, He Zhang, Junbo Tan +2
Post-training Vision-Language-Action (VLA) models into policies that can be reliably deployed on real robots remains a major bottleneck. SFT and DAgger exploit failure signals only…
Bridging Perception and Action: A Lightweight Multimodal Meta-Planner Framework for Robust Earth Observation Agents
Jinghui Xu, Boyi Shangguan, Mengke Zhu +10
Autonomous Earth Observation (EO) agents are transitioning from passive perception to complex, multi-step task execution. However, current architectures that integrate planning and…
RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting
Yucheng Xin, Jiacheng Bao, Yubo Dong +5
Humanoid robots have demonstrated impressive motor skills in a wide range of tasks, yet whole-body control for humanlike long-time, dynamic fighting remains particularly challengin…
Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot
Yucheng Xin, Jiacheng Bao, Haoran Yang +6
The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like behaviors. However, research…
PhotoAgent: A Robotic Photographer with Spatial and Aesthetic Understanding
Lirong Che, Zhenfeng Gan, Yanbo Chen +2
Embodied agents for creative tasks like photography must bridge the semantic gap between high-level language commands and geometric control. We introduce PhotoAgent, an agent that…
When to Lock Attention: Training-Free KV Control in Video Diffusion
Tianyi Zeng, Jincheng Gao, Tianyi Wang +8
Maintaining background consistency while enhancing foreground quality remains a core challenge in video editing. Injecting full-image information often leads to background artifact…
Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation
Yihao Wu, Jinming Ma, Junbo Tan +5
Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot reliably steer the policy toward…
Robust Policy Expansion for Offline-to-Online RL under Diverse Data Corruption
Longxiang He, Deheng Ye, Junbo Tan +2
Pretraining a policy on offline data followed by fine-tuning through online interactions, known as Offline-to-Online Reinforcement Learning (O2O RL), has emerged as a promising par…
A Hybrid Force-Position Strategy for Shape Control of Deformable Linear Objects With Graph Attention Networks
Yanzhao Yu, Haotian Yang, Junbo Tan +1
Manipulating deformable linear objects (DLOs) such as wires and cables is crucial in various applications like electronics assembly and medical surgeries. However, it faces challen…
Data-Driven MPC with Data Selection for Flexible Cable-Driven Robotic Arms
Huayue Liang, Yanbo Chen, Hongyang Cheng +5
Flexible cable-driven robotic arms (FCRAs) offer dexterous and compliant motion. Still, the inherent properties of cables, such as resilience, hysteresis, and friction, often lead…
A Universal Vehicle-Trailer Navigation System with Neural Kinematics and Online Residual Learning
Yanbo Chen, Yunzhe Tan, Yaojia Wang +3
Autonomous navigation of vehicle-trailer systems is crucial in environments like airports, supermarkets, and concert venues, where various types of trailers are needed to navigate…
Unlocking adaptive digital pathology through dynamic feature learning
Jiawen Li, Tian Guan, Qingxin Xia +17
Foundation models have revolutionized the paradigm of digital pathology, as they leverage general-purpose features to emulate real-world pathological practices, enabling the quanti…
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu +4
Offline Safe Reinforcement Learning (RL) seeks to address safety constraints by learning from static datasets and restricting exploration. However, these approaches heavily rely on…
AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained Optimization
Longxiang He, Li Shen, Xueqian Wang
Implicit Q-learning (IQL) serves as a strong baseline for offline RL, which learns the value function using only dataset actions through quantile regression. However, it is unclear…
Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy
Chenyang Cao, Zichen Yan, Renhao Lu +2
Offline goal-conditioned reinforcement learning (GCRL) aims at solving goal-reaching tasks with sparse rewards from an offline dataset. While prior work has demonstrated various ap…
Geometric Structure and Polynomial-time Algorithm of Game Equilibria
Hongbo Sun, Chongkun Xia, Junbo Tan +3
Whether a PTAS (polynomial-time approximation scheme) exists for game equilibria has been an open question, and its absence has indications and consequences in three fields: the pr…
DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning
Longxiang He, Li Shen, Linrui Zhang +2
Constrained policy search (CPS) is a fundamental problem in offline reinforcement learning, which is generally solved by advantage weighted regression (AWR). However, previous meth…
Visuotactile Sensor Enabled Pneumatic Device Towards Compliant Oropharyngeal Swab Sampling
Shoujie Li, Mingshan He, Wenbo Ding +5
Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining th…
Data-Driven Robust Control for Discrete Linear Time-Invariant Systems: A Descriptor System Approach
Jiabao He, Xuan Zhang, Feng Xu +2
Given the recent surge of interest in data-driven control, this paper proposes a two-step method to study robust data-driven control for a parameter-unknown linear time-invariant (…
Data-Driven Controllability Analysis and Stabilization for Linear Descriptor Systems
Jiabao He, Xuan Zhang, Feng Xu +2
For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it. First, a data-b…