Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge

Xingyu Fu; Sheng Zhang; Gukyeong Kwon; Pramuditha Perera; Henghui Zhu; Yuhao Zhang; Alexander Hanbo Li; William Yang Wang; Zhiguo Wang; Vittorio Castelli; Patrick Ng; Dan Roth; Bing Xiang

arXiv · 2305.18842

Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge

Xingyu Fu·Sheng Zhang·Gukyeong Kwon·Pramuditha Perera·Henghui Zhu·Yuhao Zhang·Alexander Hanbo Li·William Yang Wang·Zhiguo Wang·Vittorio Castelli·Patrick Ng·Dan Roth·Bing Xiang

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Abstract

The open-ended Visual Question Answering (VQA) task requires AI models to jointly reason over visual and natural language inputs using world knowledge. Recently, pre-trained Language Models (PLM) such as GPT-3 have been applied to the task and shown to be powerful world knowledge sources. However, these methods suffer from low knowledge coverage caused by PLM bias -- the tendency to generate certain tokens over other tokens regardless of prompt changes, and high dependency on the PLM quality -- only models using GPT-3 can achieve the best result. To address the aforementioned challenges, we propose RASO: a new VQA pipeline that deploys a generate-then-select strategy guided by world knowledge for the first time. Rather than following the de facto standard to train a multi-modal model that directly generates the VQA answer, RASO first adopts PLM to generate all the possible answers, and then trains a lightweight answer selection model for the correct answer. As proved in our analysis, RASO expands the knowledge coverage from in-domain training data by a large margin. We provide extensive experimentation and show the effectiveness of our pipeline by advancing the state-of-the-art by 4.1% on OK-VQA, without additional computation cost. Code and models are released at http://cogcomp.org/page/publication_view/1010

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Xingyu Fu, Sheng Zhang, Gukyeong Kwon, Pramuditha Perera, Henghui Zhu, Yuhao Zhang, Alexander Hanbo Li, William Yang Wang, Zhiguo Wang, Vittorio Castelli, Patrick Ng, Dan Roth, Bing Xiang. 2023-05-30. Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge. https://arxiv.org/abs/2305.18842

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