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Large vision-language models (LVLMs) have shown remarkable abilities in understanding visual information with human languages.
Recursive estimation of autoregressions
Edward James Hannan, AJ McDougall, and Don Stephen Poskitt · 1989
Earlier work this paper cites.
Characterizing the sequential structure of interactive behaviors through statistical and grammatical techniques
Gary M Olson, James D Herbsleb, and Henry H Reuter · 1994
Earlier work this paper cites.
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Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Im2text: Describing images using 1 million captioned photographs
Vicente Ordonez, Girish Kulkarni, and Tamara Berg · 2011
Earlier work this paper cites.
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Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
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Earlier work this paper cites.
Spice: Semantic propositional image caption evaluation
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Earlier work this paper cites.
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Earlier work this paper cites.
Beam search strategies for neural machine translation
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Earlier work this paper cites.
Object hallucination in image captioning
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Earlier work this paper cites.
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Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
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