13 citations · 25 across the 12 of their papers we have counts for
13 papers
-class groups in the cyclotomic -extension of imaginary quadratic fields
Somnath Jha, Debanjana Kundu, H. Laxmi +1
We study the structure of the -class group of the first layer of the cyclotomic -extension of an imaginary quadratic field where is non-split. We obtain restri…
Lift3D-VLA: Lifting VLA Models to 3D Geometry and Dynamics-Aware Manipulation
Jiaming Liu, Qingpo Wuwu, Nuowei Han +8
Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in physical environments fundame…
TACO: TActile World Model as a Self-COrrector for Scalable Robot Policy Post-Training
Shengbang Liu, Yueru Jia, Yuyang Yan +7
Vision-Language-Action models and World Action Models have shown promising generalization in robotic manipulation but remain fragile in contact-rich tasks, where contact perturbati…
GeneralVLA-2: Geometry-Aware Reconstruction and Governed Memory for Robot Planning
Haoyu Wang, Guoqing Ma, Zeyu Zhang +3
Generalist vision-language-action systems need object-centric 3D evidence and reusable manipulation experience to plan reliable robot trajectories. GeneralVLA provides a hierarchic…
PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models
Ziyang Chen, Shaoguang Wang, Weiyu Guo +5
Vision-Language-Action (VLA) models have achieved remarkable success in language-conditioned robotic manipulation. However, deploying these models in open-ended environments requir…
Video2Act: A Dual-System Video Diffusion Policy with Robotic Spatio-Motional Modeling
Yueru Jia, Jiaming Liu, Shengbang Liu +7
Robust perception and dynamics modeling are fundamental to real-world robotic policy learning. Recent methods employ video diffusion models (VDMs) to enhance robotic policies, impr…
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…
Fast-in-Slow: A Dual-System Foundation Model Unifying Fast Manipulation within Slow Reasoning
Hao Chen, Jiaming Liu, Chenyang Gu +8
Generalized policy and execution efficiency constitute the two critical challenges in robotic manipulation. While recent foundation policies benefit from the common-sense reasoning…
3DWG: 3D Weakly Supervised Visual Grounding via Category and Instance-Level Alignment
Xiaoqi Li, Jiaming Liu, Nuowei Han +4
The 3D weakly-supervised visual grounding task aims to localize oriented 3D boxes in point clouds based on natural language descriptions without requiring annotations to guide mode…
RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulation
Jiaming Liu, Mengzhen Liu, Zhenyu Wang +7
A fundamental objective in robot manipulation is to enable models to comprehend visual scenes and execute actions. Although existing Vision-Language-Action (VLA) models for robots…
LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding
Senqiao Yang, Jiaming Liu, Ray Zhang +7
Recently, Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have shown promise in instruction following and 2D image understanding. While these models are p…
Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation
Jiaming Liu, Ran Xu, Senqiao Yang +5
Continual Test-Time Adaptation (CTTA) is proposed to migrate a source pre-trained model to continually changing target distributions, addressing real-world dynamism. Existing CTTA…
NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu +4
Neural 3D reconstruction from multi-view images has recently attracted increasing attention from the community. Existing methods normally learn a neural field for the whole scene,…