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cs.CV2024
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images
Zhecan Wang, Junzhang Liu, Chia-Wei Tang +11
Existing vision-language understanding benchmarks largely consist of images of objects in their usual contexts. As a consequence, recent multimodal large language models can perfor…
cs.CL2024
Advancing Chart Question Answering with Robust Chart Component Recognition
Hanwen Zheng, Sijia Wang, Chris Thomas +1
Chart comprehension presents significant challenges for machine learning models due to the diverse and intricate shapes of charts. Existing multimodal methods often overlook these…
cs.CV2024
Detecting Multimodal Situations with Insufficient Context and Abstaining from Baseless Predictions
Junzhang Liu, Zhecan Wang, Hammad Ayyubi +5
Despite the widespread adoption of Vision-Language Understanding (VLU) benchmarks such as VQA v2, OKVQA, A-OKVQA, GQA, VCR, SWAG, and VisualCOMET, our analysis reveals a pervasive…