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Xuan Dong

10 accepted papers

2026

MMBench-GUI: A Unified Hierarchical Evaluation Framework for Multi-Platform GUI Agents

CVPR 2026

We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web. The benchmark spans four levels: Content Understanding, Element Grounding, Task Automation, and Task Collaboration, covering essential skills for GUI agents. T

Cited by 0SourcecodeScholar
2025

From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities

ACL 2025finding

To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints of any specific non-linguistic modality, Omni-MLLMs map various non-linguistic modalities into the embedding space of LLM…

2025

Investigating and Enhancing the Robustness of Large Multimodal Models Against Temporal Inconsistency

ACL 2025long

Large Multimodal Models (LMMs) have recently demonstrated impressive performance on general video comprehension benchmarks. Nevertheless, for broader applications, the robustness of their temporal analysis capability needs to be thoroughly investigated yet predominantly ignored. Motivated by this, w…

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2025

PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models

CVPR 2025poster

Large Vision-Language Models (VLMs) have been extended to understand both images and videos. Visual token compression is leveraged to reduce the considerable token length of visual inputs. To meet the needs of different tasks, existing high-performance models usually process images and videos separa…

2024

Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning

NeurIPS 2024poster

Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data. Despite these advances, there is no pre-training method that effectively exploits the interleaved image-text data, which is very prevalent on the Intern…

2021

An End-To-End Non-Intrusive Model for Subjective and Objective Real-World Speech Assessment Using a Multi-Task Framework

ICASSP 2021accepted

Speech assessment is crucial for many applications, but current intrusive methods cannot be used in real environments. Data-driven approaches have been proposed, but they use simulated speech materials or only estimate objective scores. In this paper, we propose a novel multi-task non-intrusive appr…

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2021

MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems

AAAI 2021technical

We study the High Dynamic Range (HDR) imaging problem using two Low Dynamic Range (LDR) images that are shot from dual-lens systems in a single shot time with different exposures. In most of the related HDR imaging methods, the problem is usually solved by Multiple Images Merging, i.e. the final HDR…

Cited by 8SourcePDFScholar
2020

An Attention Enhanced Multi-Task Model for Objective Speech Assessment in Real-World Environments

ICASSP 2020accepted

Computational objective metrics that use reference signals have been shown to be effective forms of speech assessment in simulated environments, since they are correlated with subjective listening studies. Recent efforts have been dedicated towards effective forms of reference-less assessment to mak…

Cited by 0SourceScholar