[1] Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, and Bryan Russell. Localizing moments in video with natural language. In Proceedings of the IEEE international conference on computer vision, pages 5803-5812, 2017.
[2] André Araujo, Jason Chaves, David Chen, Roland Angst, and Bernd Girod. Stanford i2v: a news video dataset for query-by-image experiments. In Proceedings of the 6th ACM Multimedia Systems Conference, pages 237-242, 2015.
[3] George Awad, Asad A Butt, Keith Curtis, Yooyoung Lee, Jonathan Fiscus, Afzal Godil, Andrew Delgado, Jesse Zhang, Eliot Godard, Lukas Diduch, et al. Trecvid 2019: An evaluation campaign to benchmark video activity detection, video captioning and matching, and video search & retrieval. arXiv preprint arXiv:2009.09984, 2020.
[4] Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman. Frozen in time: A joint video and image encoder for end-to-end retrieval. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 1728-1738, 2021.
[5] Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman. A clip-hitchhiker's guide to long video retrieval. arXiv preprint arXiv:2205.08508, 2022.
[6] Marco Baroni and Silvia Bernardini. A new approach to the study of translationese: Machine-learning the difference between original and translated text. Literary and Linguistic Computing, 21(3):259-274, 2006.
[7] Gedas Bertasius, Heng Wang, and Lorenzo Torresani. Is space-time attention all you need for video understanding? In ICML, volume 2, page 4, 2021.
[8] Aozhu Chen, Ziyuan Wang, Chengbo Dong, Kaibin Tian, Ruixiang Zhao, Xun Liang, Zhanhui Kang, and Xirong Li. Chinaopen: A dataset for open-world multimodal learning. arXiv preprint arXiv:2305.05880, 2023.
[9] David Chen and William B Dolan. Collecting highly parallel data for paraphrase evaluation. In Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, pages 190–200, 2011.
[10] Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, and William W Cohen. Murag: Multimodal retrieval-augmented generator for open question answering over images and text. arXiv preprint arXiv:2210.02928, 2022.
[11] Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev. Reproducible scaling laws for contrastive language-image learning. arXiv preprint arXiv:2212.07143, 2022.
[12] Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. Unsupervised cross-lingual representation learning at scale. arXiv preprint arXiv:1911.02116, 2019.
[13] Rishabh Dabral, Ganesh Ramakrishnan, Preethi Jyothi, et al. Rudder: A cross lingual video and text retrieval dataset. arXiv preprint arXiv:2103.05457, 2021.
[14] Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929, 2020.
[15] Joseph G Ellis, Brendan Jou, and Shih-Fu Chang. Why we watch the news: a dataset for exploring sentiment in broadcast video news. In Proceedings of the 16th international conference on multimodal interaction, pages 104-111, 2014.
[16] Han Fang, Pengfei Xiong, Luhui Xu, and Yu Chen. Clip2video: Mastering video-text retrieval via image clip. arXiv preprint arXiv:2106.11097, 2021.
[17] Yuying Ge, Yixiao Ge, Xihui Liu, Dian Li, Ying Shan, Xiaohu Qie, and Ping Luo. Bridging video-text retrieval with multiple choice questions. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 16167-16176, 2022.
[18] Ruediger Glott, Philipp Schmidt, and Rishab Ghosh. Wikipedia survey—overview of results. United Nations University: Collaborative Creativity Group, 8:1158–1178, 2010.
[19] Po-Yao Huang, Mandela Patrick, Junjie Hu, Graham Neubig, Florian Metze, and Alexander Hauptmann. Multilingual multimodal pre-training for zero-shot cross-lingual transfer of vision-language models. arXiv preprint arXiv:2103.08849, 2021.
[20] Soumya Jahagirdar, Minesh Mathew, Dimosthenis Karatzas, and CV Jawahar. Watching the news: Towards videoqa models that can read. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 4441-4450, 2023.