collaborators

23 papers

cs.CV2026

SUMO: Segment and Track Any Motion with Nonlinear State Space Models

Kexin Tian, Sixu Li, Keshu Wu +2

Visual Object Tracking (VOT) and Moving Object Segmentation (MOS) are two fundamental tasks in computer vision that involve both spatial and temporal object dynamics. Existing meth…

cs.LG2026

KANMixer: a minimal KAN-centered mixer for long-term time series forecasting

Lingyu Jiang, Dengzhe Hou, Yuping Wang +9

Long-term time series forecasting (LTSF) underpins critical applications from energy management to weather prediction, yet achieving reliable multi-step-ahead accuracy remains chal…

cs.CV2026

VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

Zhiwen Fan, Jian Zhang, Renjie Li +15

The rapid advancement of Large Multimodal Models (LMMs) for 2D images and videos has motivated extending these models to understand 3D scenes, aiming for human-like visual-spatial…

cs.CL2026

Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

Keshu Wu, Chenchen Kuai, Zihao Li +6

Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including graph- and hypergraph-based…

cs.CV2026

NexusFlow: Unifying Disparate Tasks under Partial Supervision via Invertible Flow Networks

Fangzhou Lin, Yuping Wang, Yuliang Guo +7

Partially Supervised Multi-Task Learning (PS-MTL) aims to leverage knowledge across tasks when annotations are incomplete. Existing approaches, however, have largely focused on the…

cs.CV2026

AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

Shuo Xing, Hongyuan Hua, Xiangbo Gao +10

Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeni…