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20112026
most citedStatistical Model Checking for Stochastic Hybrid Systems

85 citations · 279 across the 25 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026

VISTAQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence

Mozhgan Nasr Azadani, Yimu Wang, Yongpeng Zhu +5

Establishing a clear link between model predictions and the visual evidence that supports them is critical for transparency and reliability in multimodal reasoning, yet current mul…

cs.CV2025

How Hard Is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+

Mei Qi Tang, Sean Sedwards, Chengjie Huang +1

The impact of snowfall on 3D object detection performance remains underexplored. Conducting such an evaluation requires a dataset with sufficient labelled data from both weather co…

cs.CV2025

HAWAII: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models

Yimu Wang, Mozhgan Nasr Azadani, Sean Sedwards +1

Improving the visual understanding ability of vision-language models (VLMs) is crucial for enhancing their performance across various tasks. While using multiple pretrained visual…

cs.CV2025

LEO-MINI: An Efficient Multimodal Large Language Model using Conditional Token Reduction and Mixture of Multi-Modal Experts

Yimu Wang, Mozhgan Nasr Azadani, Sean Sedwards +1

Redundancy of visual tokens in multi-modal large language models (MLLMs) significantly reduces their computational efficiency. Recent approaches, such as resamplers and summarizers…

cs.CV2025

OV-SCAN: Semantically Consistent Alignment for Novel Object Discovery in Open-Vocabulary 3D Object Detection

Adrian Chow, Evelien Riddell, Yimu Wang +2

Open-vocabulary 3D object detection for autonomous driving aims to detect novel objects beyond the predefined training label sets in point cloud scenes. Existing approaches achieve…

cs.CV2025

Mitigating the Modality Gap: Few-Shot Out-of-Distribution Detection with Multi-modal Prototypes and Image Bias Estimation

Yimu Wang, Evelien Riddell, Adrian Chow +2

Existing vision-language model (VLM)-based methods for out-of-distribution (OOD) detection typically rely on similarity scores between input images and in-distribution (ID) text pr…