activity
20242026
collaborators

10 papers

cs.RO2026

PLS-Calib: A Partial Least Squares Framework for Event Camera and Odometry Calibration under Ground Motion Constraints

Guangyu Li, Xiao Li, Yujie Wu +5

Accurate extrinsic rotation calibration between sensors is fundamental to the performance of robotic perception systems. However, most existing calibration techniques rely on full…

cs.LG2026

Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning

Yixian Shen, Zhiheng Yang, Qi Bi +6

Multimodal spatial reasoning often relies on long chains of intermediate textual and visual thoughts, where accumulating visual tokens and dense cross-modal attention incur substan…

cs.RO2026

Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation

Xiang Fang, Wanlong Fang, Changshuo Wang

Vision-Language Navigation in Continuous Environments (VLN-CE) poses a formidable challenge for autonomous agents, requiring seamless integration of natural language instructions a…

cs.CV2026

CogniVerse: Revolutionizing Multi-Modal Retrieval-Augmented Generation with Cognitive Reflection and Geometric Reasoning

Xiang Fang, Wanlong Fang, Changshuo Wang

Multi-modal Retrieval-Augmented Generation (MMRAG) has emerged as a powerful paradigm for enhancing Multimodal Large Language Models in knowledge-intensive question answering by in…

cs.CV2026

Rethinking Video-Language Model from the Language Input Perspective

Xiang Fang, Wanlong Fang, Changshuo Wang +2

Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between videos and texts. Although…

cs.CV2026

Towards Unified Vision-Language Models with Incomplete Multi-Modal Inputs

Xiang Fang, Wanlong Fang, Changshuo Wang +4

Video-Language Models (VLMs) have demonstrated impressive multi-modal reasoning capabilities across diverse computer vision applications. However, these VLMs are task-specific and…

cs.CV2026

Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization

Xiang Fang, Wanlong Fang, Changshuo Wang

Large Vision-Language Models (LVLMs) have transformed multi-modal understanding, excelling in tasks like image captioning and visual question answering by integrating visual and te…

cs.AI2026

MMPG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning

Yusong Wang, Jialun Shen, Zhihao Wu +6

Graph Neural Networks (GNNs) have been widely adopted for Protein Representation Learning (PRL), as residue interaction networks can be naturally represented as graphs. Current GNN…

cs.CV2025

Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation

Changshuo Wang, Shuting He, Xiang Fang +3

Few-shot point cloud semantic segmentation aims to accurately segment "unseen" new categories in point cloud scenes using limited labeled data. However, pretraining-based methods n…

cs.CV2024

Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network

Xiang Fang, Wanlong Fang, Changshuo Wang +5

Given some video-query pairs with untrimmed videos and sentence queries, temporal sentence grounding (TSG) aims to locate query-relevant segments in these videos. Although previous…