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Modern image captioning models are usually trained with text similarity objectives.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams. 1992 · 1992
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BLEU: a Method for Automatic Evaluation of Machine Translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wj Wei-jing Zhu. 2002 · 2002
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ROUGE: A Package for Automatic Evaluation of Summaries
Chin-Yew Lin. 2004 · 2004
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METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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Microsoft COCO: Common Objects in Context
Tsung Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick. 2014 · 2014
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Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer. 2015 · 2015
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Deep Visual-Semantic Alignments for Generating Image Descriptions
Andrej Karpathy and Li Fei-Fei. 2015 · 2015
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CIDEr: Consensus-based Image Description Evaluation
Ramakrishna Vedantam, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Show and Tell: A Neural Image Caption Generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2015 · 2015
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Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. 2015 · 2015
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SPICE: Semantic Propositional Image Caption Evaluation
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould. 2016 · 2016
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Sequence Level Training with Recurrent Neural Networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
Cited alongside, same era.
Towards Diverse and Natural Image Descriptions via a Conditional GAN
Bo Dai, Sanja Fidler, Raquel Urtasun, and Dahua Lin. 2017 · 2017
Cited alongside, same era.
Contrastive Learning for Image Captioning
Bo Dai and Dahua Lin. 2017 · 2017
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Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chana, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017 · 2017
Cited alongside, same era.
Self-critical Sequence Training for Image Captioning
Steven J. Rennie, Etienne Marcheret, Youssef Mroueh, Jarret Ross, and Vaibhava Goel. 2017 · 2017
Cited alongside, same era.
Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut. 2018 · 2018
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
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BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2019 · 2019
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A Better Variant of Self-Critical Sequence Training
Ruotian Luo. 2020 · 2020
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HuggingFace’s Transformers: State-of-the-art Natural Language Processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2020 · 2020
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Liwei Wang, Alexander G. Schwing, and Svetlana Lazebnik. 2017 · 2017
Cited alongside, same era.
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang. 2018 · 2018
Cited alongside, same era.
Show, tell and discriminate: Image captioning by self-retrieval with partially labeled data
Xihui Liu, Hongsheng Li, Jing Shao, Dapeng Chen, and Xiaogang Wang. 2018 · 2018
Cited alongside, same era.
Discriminability Objective for Training Descriptive Captions
Ruotian Luo, Gregory Shakhnarovich, Scott Cohen, and Brian Price. 2018 · 2018
Cited alongside, same era.
ViLBERTScore: Evaluating Image Caption Using Vision-and-Language BERT
Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim, Trung Bui, and Kyomin Jung. 2020a
Cited in the paper.
CapWAP: Captioning with a Purpose
Kenton Lee, Ming-wei Chang Jonathan, and H Clark Regina. 2020b
Cited in the paper.
Later among the works it cites.
Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe. 2021 · 2021
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CLIPScore: A Reference-free Evaluation Metric for Image Captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi. 2021 · 2021
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UMIC : An Unreferenced Metric for Image Captioning via Contrastive Learning
Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt, Trung Bui, and Kyomin Jung. 2021 · 2021
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Learning Transferable Visual Models From Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever, Jong Wook, Kim Chris, Hallacy Aditya, Ramesh Gabriel, Goh Sandhini, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021
Later among the works it cites.
How Much Can CLIP Benefit Vision-and-Language Tasks?
Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, and Kurt Keutzer. 2022 · 2022
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