2 citations · 7 across the 18 of their papers we have counts for
22 papers
Trust-Calibrated VLA Policy Post-Training with Evolving Imagination
Wenzhan Li, Yiran Qin, Heng Zhou +3
Vision-Language-Action (VLA) models are often pretrained via imitation learning, making reinforcement learning (RL) post-training important when deployment moves beyond demonstrati…
Arm-wise Compositional Generalization in Dual-Arm Vision-Language-Action Models
Zaibin Zhang, Binghao Ran, Yuhan Wu +10
Generalization in multi-arm collaboration can be studied as composing familiar atomic skills in new ways across arms. However, existing evaluations offer limited insight into which…
MAAP: Multi-Agent Active Perception for Collaborative Manipulation
Bruno N. Y. Chen, Li Kang, Heng Zhou +4
Multi-agent manipulation naturally produces multiple task-driven viewpoints: every arm carries a wrist camera and moves through the scene while acting. Yet these observations are t…
MA-VLA: Multi-Arm Vision-Language-Action Model for Collaboration and Compositional Generalization
Zaibin Zhang, Junlan Xiao, Zhongbo Zhang +11
Multi-arm collaboration is becoming a core capability in embodied manipulation. Recent vision-language-action (VLA) models integrate perception, language, and control, but most rep…
Trans2Occ: Voxel Occupancy Estimation and Grasp for Transparent Objects from Simulation to Reality
Yixuan Yang, Sha Zhang, Rui Li +12
Transparent objects remain challenging for robotic perception due to unreliable depth sensing caused by refraction and reflection. While prior approaches rely on multi-view reconst…
ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation
Yiran Qin, Jiahua Ma, Li Kang +11
Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabling robots to autonomously perf…
Referring-Aware Visuomotor Policy Learning for Closed-Loop Manipulation
Jiahua Ma, Yiran Qin, Xin Wen +5
This paper addresses a fundamental problem of visuomotor policy learning for robotic manipulation: how to enhance robustness in out-of-distribution execution errors or dynamically…
CoEnv: Driving Embodied Multi-Agent Collaboration via Compositional Environment
Li Kang, Yutao Fan, Rui Li +11
Multi-agent embodied systems hold promise for complex collaborative manipulation, yet face critical challenges in spatial coordination, temporal reasoning, and shared workspace awa…
Ego to World: Collaborative Spatial Reasoning in Embodied Systems via Reinforcement Learning
Heng Zhou, Li Kang, Yiran Qin +12
Understanding the world from distributed, partial viewpoints is a fundamental challenge for embodied multi-agent systems. Each agent perceives the environment through an ego-centri…
Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge
Li Kang, Heng Zhou, Xiufeng Song +41
Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more com…
TouchGuide: Inference-Time Steering of Visuomotor Policies via Touch Guidance
Zhemeng Zhang, Jiahua Ma, Xincheng Yang +13
Fine-grained and contact-rich manipulation remain challenging for robots, largely due to the underutilization of tactile feedback. To address this, we introduce TouchGuide, a novel…
Toward Efficient Agents: Memory, Tool learning, and Planning
Xiaofang Yang, Lijun Li, Heng Zhou +12
Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has continued to improve, efficiency, whi…
CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
Jiahua Ma, Yiran Qin, Yixiong Li +3
Diffusion Policy (DP) enables robots to learn complex behaviors by imitating expert demonstrations through action diffusion. However, in practical applications, hardware limitation…
RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraints
Yiran Qin, Li Kang, Xiufeng Song +5
Designing effective embodied multi-agent systems is critical for solving complex real-world tasks across domains. Due to the complexity of multi-agent embodied systems, existing me…
NavigateDiff: Visual Predictors are Zero-Shot Navigation Assistants
Yiran Qin, Ao Sun, Yuze Hong +2
Navigating unfamiliar environments presents significant challenges for household robots, requiring the ability to recognize and reason about novel decoration and layout. Existing r…
High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation
Ziye Wang, Yiran Qin, Lin Zeng +1
Weather nowcasting is an essential task that involves predicting future radar echo sequences based on current observations, offering significant benefits for disaster management, t…
WorldSimBench: Towards Video Generation Models as World Simulators
Yiran Qin, Zhelun Shi, Jiwen Yu +10
Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based…
Story3D-Agent: Exploring 3D Storytelling Visualization with Large Language Models
Yuzhou Huang, Yiran Qin, Shunlin Lu +4
Traditional visual storytelling is complex, requiring specialized knowledge and substantial resources, yet often constrained by human creativity and creation precision. While Large…
MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control
Enshen Zhou, Yiran Qin, Zhenfei Yin +5
It is a long-lasting goal to design a generalist-embodied agent that can follow diverse instructions in human-like ways. However, existing approaches often fail to steadily follow…
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration
Chaoqun Wang, Yiran Qin, Zijian Kang +2
Recent camera-based 3D object detection is limited by the precision of transforming from image to 3D feature spaces, as well as the accuracy of object localization within the 3D sp…
MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perception
Yiran Qin, Enshen Zhou, Qichang Liu +5
It is a long-lasting goal to design an embodied system that can solve long-horizon open-world tasks in human-like ways. However, existing approaches usually struggle with compound…
SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection
Yiran Qin, Chaoqun Wang, Zijian Kang +3
In this paper, we propose a novel training strategy called SupFusion, which provides an auxiliary feature level supervision for effective LiDAR-Camera fusion and significantly boos…