Papers with open-sourced VLMs

2 papers
Red Teaming Visual Language Models (2024.findings-acl)

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Challenge: VLMs (Vision-Language Models) can be induced to generate harmful or inaccurate content through specific test cases.
Approach: They propose a red teaming dataset which encompasses 12 subtasks under 4 primary aspects (faithfulness, privacy, safety, fairness) this dataset is the first to benchmark current VLMs in terms of these 4 aspects .
Outcome: The proposed dataset shows that 10 open-source VLMs struggle with red teaming in different degrees and have up to 31% performance gap with GPT-4V.
FoodieQA: A Multimodal Dataset for Fine-Grained Understanding of Chinese Food Culture (2024.emnlp-main)

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Challenge: FoodieQA is a manually curated, fine-grained image-text dataset capturing the intricate features of food cultures across various regions in China.
Approach: They evaluate vision–language Models and large language models on unseen food images and corresponding questions.
Outcome: The proposed dataset evaluates vision–language Models and large language models on unseen food images and corresponding questions.

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