1 citations · 1 across the 17 of their papers we have counts for
17 papers
CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation
Shaoxuan Li, Xiangyu Dong, Xiaoguang Ma +3
Vision-language navigation (VLN) has recently advanced with large language and multimodal models, enabling agents to follow natural-language instructions in unseen environments wit…
Acting While Understanding: Asynchronous Semantic-Action Decoupling for Real-Time Vision-Language-Action Models
Shenhao Yan, Ge Wang, Qi Liu +7
Vision-Language-Action models (VLAs) have demonstrated strong task understanding and generalization in robotic manipulation, yet the high computational cost of full-model inference…
DUPLEX: Agentic Dual-System Planning via LLM-Driven Information Extraction
Keru Hua, Ding Wang, Yaoying Gu +1
While Large Language Models (LLMs) provide semantic flexibility for robotic task planning, their susceptibility to hallucination and logical inconsistency limits their reliability…
Hierarchical Dual-Change Collaborative Learning for UAV Scene Change Captioning
Fuhai Chen, Pengpeng Huang, Junwen Wu +4
This paper proposes a novel task for UAV scene understanding - UAV Scene Change Captioning (UAV-SCC) - which aims to generate natural language descriptions of semantic changes in d…
PM-Nav: Priori-Map Guided Embodied Navigation in Functional Buildings
Jiang Gao, Xiangyu Dong, Haozhou Li +3
Existing language-driven embodied navigation paradigms face challenges in functional buildings (FBs) with highly similar features, as they lack the ability to effectively utilize p…
ViSA-Enhanced Aerial VLN: A Visual-Spatial Reasoning Enhanced Framework for Aerial Vision-Language Navigation
Haoyu Tong, Xiangyu Dong, Xiaoguang Ma +3
Existing aerial Vision-Language Navigation (VLN) methods predominantly adopt a detection-and-planning pipeline, which converts open-vocabulary detections into discrete textual scen…
CMMR-VLN: Vision-and-Language Navigation via Continual Multimodal Memory Retrieval
Haozhou Li, Xiangyu Dong, Huiyan Jiang +2
Although large language models (LLMs) are introduced into vision-and-language navigation (VLN) to improve instruction comprehension and generalization, existing LLM- based VLN lack…
Mean-Flow based One-Step Vision-Language-Action
Yang Chen, Xiaoguang Ma, Bin Zhao
Recent advances in FlowMatching-based Vision-Language-Action (VLA) frameworks have demonstrated remarkable advantages in generating high-frequency action chunks, particularly for h…
PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking
Jiacheng Bao, Haoran Yang, Yucheng Xin +7
Humanoid robots are expected to execute agile and expressive whole-body motions in real-world settings. Existing text-to-motion generation models are predominantly trained on captu…
LightZeroNav: Zero-Shot Vision Language Navigation in Continuous Environments Based on Lightweight VLMs
Kun Luo, Xiangyu Dong, Xiaoguang Ma +2
Although vision-language navigation (VLN) has progressed rapidly, zero-shot VLN in continuous environments (VLN-CE) remains highly challenging when using lightweight vision-languag…
SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models
Xiangyu Dong, Haoran Zhao, Jiang Gao +5
Recent advances in vision-language navigation (VLN) were mainly attributed to emerging large language models (LLMs). These methods exhibited excellent generalization capabilities i…
Subconscious Robotic Imitation Learning
Jun Xie, Zhicheng Wang, Jianwei Tan +2
Although robotic imitation learning (RIL) is promising for embodied intelligent robots, existing RIL approaches rely on computationally intensive multi-model trajectory predictions…
Constrained Behavior Cloning for Robotic Learning
Wensheng Liang, Jun Xie, Zhicheng Wang +2
Behavior cloning (BC) is a popular supervised imitation learning method in the societies of robotics, autonomous driving, etc., wherein complex skills can be learned by direct imit…
Group-Mix SAM: Lightweight Solution for Industrial Assembly Line Applications
Wu Liang, X. -G. Ma
Since the advent of the Segment Anything Model(SAM) approximately one year ago, it has engendered significant academic interest and has spawned a large number of investigations and…
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification
Shuai Li, Xiaoguang Ma, Shancheng Jiang +1
Remarkable successes were made in Medical Image Classification (MIC) recently, mainly due to wide applications of convolutional neural networks (CNNs). However, adversarial example…
ALow-Cost Real-Time Framework for Industrial Action Recognition Using Foundation Models
Zhicheng Wang, Wensheng Liang, Ruiyan Zhuang +3
Action recognition (AR) in industrial environments -- particularly for identifying actions and operational gestures -- faces persistent challenges due to high deployment costs, poo…
Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics
Shuai Li, Xiaoyu Jiang, Xiaoguang Ma
Deep neural networks were significantly vulnerable to adversarial examples manipulated by malicious tiny perturbations. Although most conventional adversarial attacks ensured the v…