activity
20232026
most citedMoE-LLaVA: Mixture of Experts for Large Vision-Language Models

34 citations · 95 across the 17 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CV2025

Malicious Image Analysis via Vision-Language Segmentation Fusion: Detection, Element, and Location in One-shot

Sheng Hang, Chaoxiang He, Hongsheng Hu +5

Detecting illicit visual content demands more than image-level NSFW flags; moderators must also know what objects make an image illegal and where those objects occur. We introduce…

cs.CV2025

Does Understanding Inform Generation in Unified Multimodal Models? From Analysis to Path Forward

Yuwei Niu, Weiyang Jin, Jiaqi Liao +7

Recent years have witnessed significant progress in Unified Multimodal Models, yet a fundamental question remains: Does understanding truly inform generation in Unified Multimodal…

cs.CV2025

A benchmark multimodal oro-dental dataset for large vision-language models

Haoxin Lv, Ijazul Haq, Jin Du +7

The advancement of artificial intelligence in oral healthcare relies on the availability of large-scale multimodal datasets that capture the complexity of clinical practice. In thi…

cs.CV2025

FlashI2V: Fourier-Guided Latent Shifting Prevents Conditional Image Leakage in Image-to-Video Generation

Yunyang Ge, Xinhua Cheng, Chengshu Zhao +5

In Image-to-Video (I2V) generation, a video is created using an input image as the first-frame condition. Existing I2V methods concatenate the full information of the conditional i…

cs.CV2025★ 4 cited

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

Yuwei Niu, Munan Ning, Mengren Zheng +9

Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evaluation standards predominantly focus on…