27 citations · 32 across the 15 of their papers we have counts for
16 papers
Skeleton-Grounded Latent Action Model for Robot World Models
Qi Lv, Jiayi Lin, Yuxin Jiang +3
Robot world models simulate how environments evolve in response to robot actions. Latent action models enable learning dynamics from videos by encoding visual transitions as proxy…
Hermite Curves as Trajectory Priors for Vision-Language-Action Models
Qi Lv, Jianming Xing, Zhao Yang +5
Despite recent progress in Vision-Language-Action (VLA) models for robotic manipulation, the action chunk remains a weakly structured interface. Existing work typically flatten eac…
Technical Report of RoboSpatial Challenge at CVPR 2026: Selective Reasoning Activation and Reference-Frame Disambiguation for Embodied Spatial Reasoning
Yuxiang Xie, Qi Lv, Jianming Xing +4
Vision-language models achieve strong general perception but often struggle with the spatial reasoning required for embodied tasks. We present RoboSpatialBrain, our submission to t…
Efficient Visual Pointing for Embodied AI:Agent-Driven Data Synthesis, Cross-Block Attention, and Iterative Correction
Zijian Hong, Qi Lv, Yuxiang Xie +4
Visual pointing maps a language instruction to pixel co ordinates, a core skill for embodied AI. We describe our PointArena 2026 solution, which achieves 77.2% overall accuracy and…
Cortical Policy: A Dual-Stream View Transformer for Robotic Manipulation
Xuening Zhang, Qi Lv, Xiang Deng +3
View transformers process multi-view observations to predict actions and have shown impressive performance in robotic manipulation. Existing methods typically extract static visual…
F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions
Qi Lv, Weijie Kong, Hao Li +7
Executing language-conditioned tasks in dynamic visual environments remains a central challenge in embodied AI. Existing Vision-Language-Action (VLA) models predominantly adopt rea…
Adaptive Sparse Softmax: An Effective and Efficient Softmax Variant
Qi Lv, Lei Geng, Ziqiang Cao +4
Softmax with the cross entropy loss is the standard configuration for current neural classification models. The gold score for a target class is supposed to be 1, but it is never r…
EO-1: An Open Unified Embodied Foundation Model for General Robot Control
Delin Qu, Haoming Song, Qizhi Chen +13
The human ability to seamlessly perform multimodal reasoning and physical interaction in the open world is a core goal for general purpose embodied intelligent systems. Recent visi…
STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
Hao Li, Qi Lv, Rui Shao +4
Transforming complex actions into discrete skill abstractions has demonstrated strong potential for robotic manipulation. Existing approaches mainly leverage latent variable models…
Spatial-Temporal Graph Diffusion Policy with Kinematic Modeling for Bimanual Robotic Manipulation
Qi Lv, Hao Li, Xiang Deng +6
Despite the significant success of imitation learning in robotic manipulation, its application to bimanual tasks remains highly challenging. Existing approaches mainly learn a poli…
3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds
Hengshuo Chu, Xiang Deng, Qi Lv +4
3D Affordance detection is a challenging problem with broad applications on various robotic tasks. Existing methods typically formulate the detection paradigm as a label-based sema…
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL
Qi Lv, Xiang Deng, Gongwei Chen +2
While the conditional sequence modeling with the transformer architecture has demonstrated its effectiveness in dealing with offline reinforcement learning (RL) tasks, it is strugg…
RoboMP: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models
Qi Lv, Hao Li, Xiang Deng +3
Multimodal Large Language Models (MLLMs) have shown impressive reasoning abilities and general intelligence in various domains. It inspires researchers to train end-to-end MLLMs or…
RSpell: Retrieval-augmented Framework for Domain Adaptive Chinese Spelling Check
Siqi Song, Qi Lv, Lei Geng +2
Chinese Spelling Check (CSC) refers to the detection and correction of spelling errors in Chinese texts. In practical application scenarios, it is important to make CSC models have…
Visual Subtitle Feature Enhanced Video Outline Generation
Qi Lv, Ziqiang Cao, Wenrui Xie +10
With the tremendously increasing number of videos, there is a great demand for techniques that help people quickly navigate to the video segments they are interested in. However, c…
General and Domain Adaptive Chinese Spelling Check with Error Consistent Pretraining
Qi Lv, Ziqiang Cao, Lei Geng +3
The lack of label data is one of the significant bottlenecks for Chinese Spelling Check (CSC). Existing researches use the method of automatic generation by exploiting unlabeled da…