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Visually Dehallucinative Instruction Generation: Know What You Don't Know

Visually Dehallucinative Instruction Generation: Know What You Don't Know [paper] <br> Sungguk Cha, Jusung Lee, Younghyun Lee and Cheoljong Yang

<img src="images/categories.png"> <br>

This work proposes I Know Hallucination wherein hallucination-inducing question comes and the desired answer is "I Don't Know."

IDK-Instructions

<img src="images/qualitative.png"> <br> Qualitative results on hallucination inducing-questions.

Prepare COCO images in advance.

IDK-Instructions uses "<image>" for the image token.

{
        "image": "MSCOCO/images/train2014/COCO_train2014_000000393224.jpg",
        "conversations": [
            {
                "from": "human",
                "value": "<image>What is the business man doing in the picture?"
            },
            {
                "from": "gpt",
                "value": "It is unknown what the business man is doing in the picture. It could be waiting, standing, walking or frowning."
            },
            {
                "from": "human",
                "value": "What is the business man doing in the picture?"
            },
            {
                "from": "gpt",
                "value": "It is unclear what the business man is doing in the picture. He could be waiting, standing, walking, or even frowning or pouting."
            }
        ]
    },

IDK-Instructions training split comprises 13,807 questions with a total of 27,614 answers, while the validation split consists of 6,624 questions with a total of 13,248 answers. Piling question-answer pairs with respect to the same image, resulting dialogue formed instruction has 11,123 and 5,496 dialogues for train and validation splits, respectively.

VQAv2-IDK

<img src="images/vqav2idk.png"> <br>

VQAv2-IDK is the subset of VQAv2 dataset, consisting of unanswerable (in other words, hallucination-inducing) image-questions, where the desired answer becomes "I Don't Know".

Citation

If you find it useful for your research and applications, please cite using this BibTeX:

@inproceedings{cha2024visually,
      title={Visually Dehallucinative Instruction Generation: Know What You Don't Know}, 
      author={Cha, Sungguk and Lee, Jusung and Lee, Younghyun and Yang, Cheoljong},
      year={2024},
}

Licenses

This work used VQAv2 dataset (CC BY 4.0 DEED license) for the question-answer source and ChatGPT for IDK-Instructions generation (refer OpenAI policies, https://openai.com/policies).