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Improving Text-to-Image Consistency via Automatic Prompt Optimization.

, , , , , , , , и . CoRR, (2024)

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Deepashri Agrawal

Aishwarya Thiruvengadam

Mukesh Agrawal

Mudit Agrawal

Hemant Agrawal

 

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MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting., , , , , и . EACL, стр. 2515-2540. Association for Computational Linguistics, (2023)Improving Text-to-Image Consistency via Automatic Prompt Optimization., , , , , , , , и . CoRR, (2024)Measuring Progress in Fine-grained Vision-and-Language Understanding., , , , и . ACL (1), стр. 1559-1582. Association for Computational Linguistics, (2023)Improving Automatic VQA Evaluation Using Large Language Models., , и . AAAI, стр. 4171-4179. AAAI Press, (2024)Improving Automatic VQA Evaluation Using Large Language Models., , и . CoRR, (2023)An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics., и . CoRR, (2023)Analyzing the Behavior of Visual Question Answering Models., , и . EMNLP, стр. 1955-1960. The Association for Computational Linguistics, (2016)Vision-Language Pretraining: Current Trends and the Future., , и . ACL (tutorial), стр. 38-43. Association for Computational Linguistics, (2022)Visual Question Answering and Beyond.. Georgia Institute of Technology, Atlanta, GA, USA, (2020)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/62277).Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization., , , , , , и . EACL (Findings), стр. 1171-1196. Association for Computational Linguistics, (2023)