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Charts are very popular to analyze data and convey important insights.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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Figure captioning with reasoning and sequence-level training
Charles Chen, Ruiyi Zhang, Eunyee Koh, Sungchul Kim, Scott Cohen, Tong Yu, Ryan A. Rossi, and Razvan C. Bunescu. 2019 · 1906
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Ankit Chadha and Rewa Sood. 2019 · 1912
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Unifying vision-and-language tasks via text generation
Jaemin Cho, Jie Lei, Hao Tan, and Mohit Bansal. 2021 · 1942
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Describing complex charts in natural language: A caption generation system
Vibhu O. Mittal, Johanna D. Moore, Giuseppe Carenini, and Steven Roth. 1998 · 1998
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Collective content selection for concept-to-text generation
Regina Barzilay and Mirella Lapata. 2005 · 2005
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Overview of duc 2005
Hoa Trang Dang. 2005 · 2005
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Choosing words in computer-generated weather forecasts
Ehud Reiter, Somayajulu Sripada, Jim Hunter, Jin Yu, and Ian Davy. 2005 · 2005
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z Li, Madian Khabsa, Han Fang, and Hao Ma. 2020 · 2006
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Computing krippendorff’s alpha-reliability
Klaus Krippendorff. 2011 · 2011
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Summarizing information graphics textually
Seniz Demir, Sandra Carberry, and Kathleen F. McCoy. 2012 · 2012
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Evaluating a tool for improving accessibility to charts and graphs
Leo Ferres, Gitte Lindgaard, Livia Sumegi, and Bruce Tsuji. 2013 · 2013
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Visualization analysis and design
Tamara Munzner. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 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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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
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What to talk about and how? selective generation using lstms with coarse-to-fine alignment
Hongyuan Mei, TTI UChicago, Mohit Bansal, and Matthew R Walter. 2016 · 2016
Cited alongside, same era.
Dynamic coattention networks for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2016 · 2016
Cited alongside, same era.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick. 2017 · 2017
Cited alongside, same era.
Figureqa: An annotated figure dataset for visual reasoning
Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Ákos Kádár, Adam Trischler, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Diversity driven attention model for query-based abstractive summarization
Preksha Nema, Mitesh M Khapra, Anirban Laha, and Balaraman Ravindran. 2017 · 2017
Cited alongside, same era.
Answering questions about charts and generating visual explanations
Dae Hyun Kim, Enamul Hoque, and Maneesh Agrawala. 2020 · 2020
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WSL-DS: Weakly supervised learning with distant supervision for query focused multi-document abstractive summarization
Md Tahmid Rahman Laskar, Enamul Hoque, and Jimmy Xiangji Huang. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Plotqa: Reasoning over scientific plots
Nitesh Methani, Pritha Ganguly, Mitesh M. Khapra, and Pratyush Kumar. 2020 · 2020
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Chart-to-text: Generating natural language descriptions for charts by adapting the transformer model
Jason Obeid and Enamul Hoque. 2020 · 2020
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Graph-structured representations for visual question answering
Damien Teney, Lingqiao Liu, and Anton van den Hengel. 2017 · 2017
Cited alongside, same era.
Challenges in data-to-document generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2017 · 2017
Cited alongside, same era.
Reference-aware language models
Zichao Yang, Phil Blunsom, Chris Dyer, and Wang Ling. 2017 · 2017
Cited alongside, same era.
Tal Baumel, Matan Eyal, and Michael Elhadad. 2018 · 2018
Cited alongside, same era.
DVQA: understanding data visualizations via question answering
Kushal Kafle, Scott Cohen, Brian L. Price, and Christopher Kanan. 2018 · 2018
Cited alongside, same era.
A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
Cited alongside, same era.
Know what you don’t know: Unanswerable questions for squad
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
Cited alongside, same era.
Totto: A controlled table-to-text generation dataset
Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, and Dipanjan Das. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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STL-CQA: Structure-based transformers with localization and encoding for chart question answering
Hrituraj Singh and Sumit Shekhar. 2020 · 2020
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Neural data-driven captioning of time-series line charts
Andrea Spreafico and Giuseppe Carenini. 2020 · 2020
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Data augmentation for abstractive query-focused multi-document summarization
Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, and Jianfeng Gao. 2021 · 2021
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Focused attention improves document grounded generation
Shrimai Prabhumoye, Kazuma Hashimoto, Yingbo Zhou, Alan W Black, and Ruslan Salakhutdinov. 2021 · 2021
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Multimodalqa: Complex question answering over text, tables and images
Alon Talmor, Ori Yoran, Amnon Catav, Dan Lahav, Yizhong Wang, Akari Asai, Gabriel Ilharco, Hannaneh Hajishirzi, and Jonathan Berant. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Qmsum: A new benchmark for query-based multi-domain meeting summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, and Dragomir Radev. 2021 · 2021
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Chart question answering: State of the art and future directions
Enamul Hoque, Kavehzadeh Parsa, and Ahmed Masry. 2022 · 2022
Closest in time.
ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque. 2022 · 2022
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Yuhuai Wu, Markus N Rabe, DeLesley Hutchins, and Christian Szegedy. 2022 · 2022
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Logic2Text: High-fidelity natural language generation from logical forms
Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou, Yunkai Zhang, Sairam Sundaresan, and William Yang Wang. 2020b · 2096
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Logic2text: High-fidelity natural language generation from logical forms
Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou, Yunkai Zhang, Sairam Sundaresan, and William Yang Wang. 2020c · 2096
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