13 papers
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…
MINOS: A Multimodal Evaluation Model for Bidirectional Generation Between Image and Text
Junzhe Zhang, Huixuan Zhang, Xinyu Hu +4
Evaluation is important for multimodal generation tasks, while traditional multimodal evaluation metrics suffer from several limitations. With the rapid progress of MLLMs, there is…
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…
UniAIDet: A Unified and Universal Benchmark for AI-Generated Image Content Detection and Localization
Huixuan Zhang, Xiaojun Wan
With the rapid proliferation of image generative models, the authenticity of digital images has become a significant concern. While existing studies have proposed various methods f…
MT2IBench: A Large-Scale Multi-Category, Multi-Instance, Multi-Relation Text-to-Image Benchmark
Huixuan Zhang, Xiaojun Wan
Text-to-image models are known to struggle with generating images that perfectly align with textual prompts. Several previous studies have focused on evaluating image-text alignmen…
JointCQ: Improving Factual Hallucination Detection with Joint Claim and Query Generation
Fan Xu, Huixuan Zhang, Zhenliang Zhang +2
Current large language models (LLMs) often suffer from hallucination issues, i,e, generating content that appears factual but is actually unreliable. A typical hallucination detect…