6 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation
Pengfei Zhou, Xiaopeng Peng, Jiajun Song +15
Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a ch…
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping
Yue Yang, Shuibai Zhang, Wenqi Shao +4
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across multimodal tasks such as visual perception and reasoning, leading to good performance on vario…
PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Models
Fanqing Meng, Wenqi Shao, Lixin Luo +8
Text-to-image (T2I) models have made substantial progress in generating images from textual prompts. However, they frequently fail to produce images consistent with physical common…
Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability,Reproducibility, and Practicality
Tianle Zhang, Langtian Ma, Yuchen Yan +9
Recent text-to-video (T2V) technology advancements, as demonstrated by models such as Gen2, Pika, and Sora, have significantly broadened its applicability and popularity. Despite t…
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Kaining Ying, Fanqing Meng, Jin Wang +19
Large Vision-Language Models (LVLMs) show significant strides in general-purpose multimodal applications such as visual dialogue and embodied navigation. However, existing multimod…