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The recent advancements in large language models (LLMs) and pre-trained vision models have accelerated the development of vision-language large models (VLLMs), enhancing the interaction between visual and linguistic modalities.
Markov decision processes: discrete stochastic dynamic programming
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Linearized two-layers neural networks in high dimension
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Clipscore: A reference-free evaluation metric for image captioning
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Llama: Open and efficient foundation language models
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How many unicorns are in this image? a safety evaluation benchmark for vision llms
Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, and Cihang Xie · 2023
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Evaluation and analysis of hallucination in large vision-language models
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Woodpecker: Hallucination correction for multimodal large language models
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Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
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Ali-agent: Assessing llms’ alignment with human values via agent-based evaluation
Jingnan Zheng, Han Wang, An Zhang, Tai D. Nguyen, Jun Sun, and Tat-Seng Chua · 2024
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