Built on

Cognitive graph for multi-hop reading comprehension at scale
Original
Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. 2019 · 1905
Earlier work this paper cites.
Latent retrieval for weakly supervised open domain question answering
Original
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 1906
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, M. Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Tabfact: A large-scale dataset for table-based fact verification
Original
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, and William Yang Wang. 2019b · 1909
Earlier work this paper cites.
Multi-hop question answering via reasoning chains
Original
Jifan Chen, Shih-ting Lin, and Greg Durrett. 2019a · 1910
Earlier work this paper cites.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Original
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
Learning to retrieve reasoning paths over wikipedia graph for question answering
Original
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. 2019 · 1911
Earlier work this paper cites.
Hierarchical graph network for multi-hop question answering
Original
Yuwei Fang, Siqi Sun, Zhe Gan, Rohit Pillai, Shuohang Wang, and Jingjing Liu. 2019 · 1911
Earlier work this paper cites.
Longformer: The long-document transformer
Original
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.

Similar

Hybridqa: A dataset of multi-hop question answering over tabular and textual data
Original
Wenhu Chen, Hanwen Zha, Zhiyu Chen, Wenhan Xiong, Hong Wang, and William Wang. 2020b · 2004
Cited alongside, same era.
Learning to recover reasoning chains for multi-hop question answering via cooperative games
Original
Yufei Feng, Mo Yu, Wenhan Xiong, Xiaoxiao Guo, Junjie Huang, Shiyu Chang, Murray Campbell, M. Greenspan, and Xiao-Dan Zhu. 2020 · 2004
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Original
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2004
Cited alongside, same era.
Open question answering over tables and text
Original
Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Wang, and William W Cohen. 2020a · 2010
Cited alongside, same era.

Then

Question answering by reasoning across documents with graph convolutional networks
Original
Nicola De Cao, Wilker Aziz, and Ivan Titov. 2018 · 2018
Later among the works it cites.
Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Original
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task
Original
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, et al. 2018 · 2018
Later among the works it cites.
Zero-shot entity linking with dense entity retrieval

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2022

Reasoning over Hybrid Chain for Table-and-Text Open Domain QA

Zhong, Wanjun, Huang, Junjie, Liu, Qian et al.

Understand

Tabular and textual question answering requires systems to perform reasoning over heterogeneous information, considering table structure, and the connections among table and text.

In this paper, we propose a ChAin-centric Reasoning and Pre-training framework (CARP).
CARP utilizes hybrid chain to model the explicit intermediate reasoning process across table and text for question answering.
We also propose a novel chain-centric pre-training method, to enhance the pre-trained model in identifying the cross-modality reasoning process and alleviating the data sparsity problem.

Built on

Cognitive graph for multi-hop reading comprehension at scale
Original
Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. 2019 · 1905
Earlier work this paper cites.
Latent retrieval for weakly supervised open domain question answering
Original
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 1906
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Original
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, M. Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Tabfact: A large-scale dataset for table-based fact verification
Original
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, and William Yang Wang. 2019b · 1909
Earlier work this paper cites.
Multi-hop question answering via reasoning chains
Original
Jifan Chen, Shih-ting Lin, and Greg Durrett. 2019a · 1910
Earlier work this paper cites.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Original
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
Learning to retrieve reasoning paths over wikipedia graph for question answering
Original
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. 2019 · 1911
Earlier work this paper cites.
Hierarchical graph network for multi-hop question answering
Original
Yuwei Fang, Siqi Sun, Zhe Gan, Rohit Pillai, Shuohang Wang, and Jingjing Liu. 2019 · 1911
Earlier work this paper cites.
Longformer: The long-document transformer
Original
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.

Similar

Hybridqa: A dataset of multi-hop question answering over tabular and textual data
Original
Wenhu Chen, Hanwen Zha, Zhiyu Chen, Wenhan Xiong, Hong Wang, and William Wang. 2020b · 2004
Cited alongside, same era.
Learning to recover reasoning chains for multi-hop question answering via cooperative games
Original
Yufei Feng, Mo Yu, Wenhan Xiong, Xiaoxiao Guo, Junjie Huang, Shiyu Chang, Murray Campbell, M. Greenspan, and Xiao-Dan Zhu. 2020 · 2004
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Original
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2004
Cited alongside, same era.
Open question answering over tables and text
Original
Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Wang, and William W Cohen. 2020a · 2010
Cited alongside, same era.

Then

Question answering by reasoning across documents with graph convolutional networks
Original
Nicola De Cao, Wilker Aziz, and Ivan Titov. 2018 · 2018
Later among the works it cites.
Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Later among the works it cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Original
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task
Original
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, et al. 2018 · 2018
Later among the works it cites.
Zero-shot entity linking with dense entity retrieval