activity
20242026
most citedPoIFusion: Multi-Modal 3D Object Detection via Fusion at Points of Interest

3 citations · 3 across the 20 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

WAM-OPD: Sharpening World Action Models via On-Policy Distillation

Panjun Liu, Xiaohan Lei, Shiqi Zhang +8

Pretrained world action models (WAMs) provide generalist capabilities across diverse robotic manipulation tasks, yet improving target-task performance to an expert level without de…

cs.RO2026

DriftingVLA: Native One-Step Vision-Language-Action Generation via Per-Dimension Temporal Drifting

Yuxuan Gao, Shiqi Zhang, Yedong Shen +6

Conventional flow-based vision-language-action (VLA) models support expressive continuous action generation but rely on multi-step refinement to produce each action chunk, increasi…

cs.CV2026

GenFirst: Generation Before Reconstruction for Stable End-to-End Latent Generative Modeling

Guangting Zheng, Yiyuan Zhang, Tao Yang +4

Latent generative models typically follow a two-stage pipeline, training a variational autoencoder for reconstruction and then a generative model on the frozen latent space. Since…

cs.CV2026

RoMAN-Flow: Taming Autoregressive Normalizing Flows for Offline Reinforcement Learning in Robotic Manipulation

Shaoxuan Wang, Guangting Zheng, Rui Huang +4

Offline reinforcement learning improves robotic policies using previously collected data without further environment interaction. Yet prevalent diffusion- and flow-matching robot p…

cs.RO2026

LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories

Zhipeng Tang, Sihang Chen, Sha Zhang +11

Autonomous laboratories hold great promise for accelerating scientific discovery. To achieve this vision, robots are supposed to dexterously manipulate diverse labware and instrume…

cs.RO2026

ReTouch: Empowering Contact-Rich Dexterous Manipulation with Online-Refined Tactile Prediction

Shiqi Zhang, Xin Zhang, Yedong Shen +9

Fusing tactile signals has proven effective for contact-rich manipulation, enabling robots to perceive contact states and adapt to rapidly changing physical interactions. Yet effec…

cs.CV2026

ThinkAfford: Affordance-Centric Reasoning for Fine-Grained 3D Grounding in Cluttered Scenes

Xinrui Lin, Sha Zhang, Shumin Wang +3

Task-driven 3D affordance grounding aims to localize the functional region in a cluttered 3D scene that enables an action specified by a natural-language instruction. Existing meth…

cs.CV2026

ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models

Haojie Ren, Songrui Luo, Lingfeng Wang +6

LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents. However, current BEV represe…

cs.RO2026

GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation

Yuan Zhang, Shiqi Zhang, Yedong Shen +11

Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot emb…

cs.CV2026

GA-GS: Generation-Assisted Gaussian Splatting for Static Scene Reconstruction

Yedong Shen, Shiqi Zhang, Sha Zhang +6

Reconstructing static 3D scene from monocular video with dynamic objects is important for numerous applications such as virtual reality and autonomous driving. Current approaches t…

cs.RO2026

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

Yuxuan Gao, Yedong Shen, Shiqi Zhang +6

Diffusion policies effectively model multimodal action distributions for robotic manipulation, but their iterative denoising requires tens to hundreds of network function evaluatio…

cs.RO2026

Learning Surgical Robotic Manipulation with 3D Spatial Priors

Yu Sheng, Lidian Wang, Xiaomeng Chu +6

Achieving 3D spatial awareness is crucial for surgical robotic manipulation, where precise and delicate operations are required. Existing methods either explicitly reconstruct the…

cs.AI2026

Environment-Aware Adaptive Pruning with Interleaved Inference Orchestration for Vision-Language-Action Models

Yuting Huang, Leilei Ding, Zhipeng Tang +7

While Vision-Language-Action (VLA) models hold promise in embodied intelligence, their large parameter counts lead to substantial inference latency that hinders real-time manipulat…