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Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization.

, , , , , , and . EACL (Findings), page 1171-1196. Association for Computational Linguistics, (2023)

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Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning., , , , , and . CoRR, (2018)Resolving vision and language ambiguities together: Joint segmentation & prepositional attachment resolution in captioned scenes., , , , , , and . Comput. Vis. Image Underst., (2017)Investigating Prompting Techniques for Zero- and Few-Shot Visual Question Answering., , and . CoRR, (2023)MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting., , , , , and . EACL, page 2515-2540. Association for Computational Linguistics, (2023)Measuring Progress in Fine-grained Vision-and-Language Understanding., , , , and . ACL (1), page 1559-1582. Association for Computational Linguistics, (2023)Improving Text-to-Image Consistency via Automatic Prompt Optimization., , , , , , , , and . CoRR, (2024)Visual Question Answering and Beyond.. Georgia Institute of Technology, Atlanta, GA, USA, (2020)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/62277).An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics., and . EACL (Findings), page 196-208. Association for Computational Linguistics, (2024)Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization., , , , , , and . EACL (Findings), page 1171-1196. Association for Computational Linguistics, (2023)Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes., , , , , , and . EMNLP, page 1493-1503. The Association for Computational Linguistics, (2016)