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20242026
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cs.CV2026

DMC-CF: Dynamic Multimodal CounterFactual QA benchmark for Causal Reasoning

Junzhe Zhang, Huixuan Zhang, Guirong Wang +5

With the rapid advancement of multimodal large language models (MLLMs), models have demonstrated increasingly powerful multimodal capabilities. However, whether MLLMs trained throu…

cs.CV2025

KBE-DME: Dynamic Multimodal Evaluation via Knowledge Enhanced Benchmark Evolution

Junzhe Zhang, Huixuan Zhang, Xiaojun Wan

The rapid progress of multimodal large language models (MLLMs) calls for more reliable evaluation protocols. Existing static benchmarks suffer from the potential risk of data conta…

cs.CV2025

How Much To Guide: Revisiting Adaptive Guidance in Classifier-Free Guidance Text-to-Vision Diffusion Models

Huixuan Zhang, Junzhe Zhang, Xiaojun Wan

With the rapid development of text-to-vision generation diffusion models, classifier-free guidance has emerged as the most prevalent method for conditioning. However, this approach…

cs.CV20241 cited

MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency

Junzhe Zhang, Huixuan Zhang, Xunjian Yin +4

Multimodal large language models (MLLMs) are prone to non-factual or outdated knowledge issues, which can manifest as misreading and misrecognition errors due to the complexity of…

cs.CV2024

EAMA : Entity-Aware Multimodal Alignment Based Approach for News Image Captioning

Junzhe Zhang, Huixuan Zhang, Xunjian Yin +1

News image captioning requires model to generate an informative caption rich in entities, with the news image and the associated news article. Current MLLMs still bear limitations…