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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)Measuring Progress in Fine-grained Vision-and-Language Understanding., , , , и . ACL (1), стр. 1559-1582. Association for Computational Linguistics, (2023)Improving Text-to-Image Consistency via Automatic Prompt Optimization., , , , , , , , и . CoRR, (2024)Decompose and Compare Consistency: Measuring VLMs' Answer Reliability via Task-Decomposition Consistency Comparison., , и . CoRR, (2024)An Introduction to Vision-Language Modeling., , , , , , , , , и 31 other автор(ы). CoRR, (2024)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)An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics., и . CoRR, (2023)Improving Automatic VQA Evaluation Using Large Language Models., , и . CoRR, (2023)Improving Automatic VQA Evaluation Using Large Language Models., , и . AAAI, стр. 4171-4179. AAAI Press, (2024)