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Question answering over heterogeneous data requires reasoning over diverse sources of data, which is challenging due to the large scale of information and organic coupling of heterogeneous data.
Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang. 2015 · 2015
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
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Wenhu Chen, Hanwen Zha, Zhiyu Chen, Wenhan Xiong, Hong Wang, and William Yang Wang. 2020b · 2020
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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. 2020 · 2020
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Mate: Multi-view attention for table transformer efficiency
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Multi-instance training for question answering across table and linked text
Vishwajeet Kumar, Saneem Chemmengath, Yash Gupta, Jaydeep Sen, Samarth Bharadwaj, and Soumen Chakrabarti. 2021 · 2021
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Tsqa: tabular scenario based question answering
Xiao Li, Yawei Sun, and Gong Cheng. 2021 · 2021
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Unsupervised multi-hop question answering by question generation
Liangming Pan, Wenhu Chen, Wenhan Xiong, Min-Yen Kan, and William Yang Wang. 2021 · 2021
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Mimoqa: Multimodal input multimodal output question answering
Hrituraj Singh, Anshul Nasery, Denil Mehta, Aishwarya Agarwal, Jatin Lamba, and Balaji Vasan Srinivasan. 2021 · 2021
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End-to-end multihop retrieval for compositional question answering over long documents
Haitian Sun, William W Cohen, and Ruslan Salakhutdinov. 2021 · 2021
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Tat-qa: A question answering benchmark on a hybrid of tabular and textual content in finance
Fengbin Zhu, Wenqiang Lei, Youcheng Huang, Chao Wang, Shuo Zhang, Jiancheng Lv, Fuli Feng, and Tat-Seng Chua. 2021 · 2021
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Mumuqa: Multimedia multi-hop news question answering via cross-media knowledge extraction and grounding
Revant Gangi Reddy, Xilin Rui, Manling Li, Xudong Lin, Haoyang Wen, Jaemin Cho, Lifu Huang, Mohit Bansal, Avirup Sil, Shih-Fu Chang, et al. 2022 · 2022
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Muger2: Multi-granularity evidence retrieval and reasoning for hybrid question answering
Yingyao Wang, Junwei Bao, Chaoqun Duan, Youzheng Wu, Xiaodong He, and Tiejun Zhao. 2022 · 2022
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Turning tables: Generating examples from semi-structured tables for endowing language models with reasoning skills
Ori Yoran, Alon Talmor, and Jonathan Berant. 2022 · 2022
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Pal: Program-aided language models
Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig. 2023 · 2023
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Mafid: Moving average equipped fusion-in-decoder for question answering over tabular and textual data
Sung-Min Lee, Eunhwan Park, Daeryong Seo, Donghyeon Jeon, Inho Kang, and Seung-Hoon Na. 2023 · 2023
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Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W Cohen. 2022 · 2022
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Binding language models in symbolic languages
Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, et al. 2022 · 2022
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Multi-hop open-domain question answering over structured and unstructured knowledge
Yue Feng, Zhen Han, Mingming Sun, and Ping Li. 2022 · 2022
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Open question answering over tables and text
Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, and William W Cohen. 2020a
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Mmhqa-icl: Multimodal in-context learning for hybrid question answering over text, tables and images
Weihao Liu, Fangyu Lei, Tongxu Luo, Jiahe Lei, Shizhu He, Jun Zhao, and Kang Liu. 2023 · 2023
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al. 2023 · 2023
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Enhancing multi-modal multi-hop question answering via structured knowledge and unified retrieval-generation
Qian Yang, Qian Chen, Wen Wang, Baotian Hu, and Min Zhang. 2023 · 2023
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