SlowGuess/NAACL_2022_OCR huggingface dataset:
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018. HotpotQA: A dataset for diverse, explainable multi-hop question answering. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2369-2380, Brussels, Belgium. Association for Computational Linguistics.
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019. Graph convolutional networks for text classification. In Proceedings of the AAAI conference on artificial intelligence, volume 33, pages 7370-7377.
Wen-tau Yih, Matthew Richardson, Chris Meek, Ming-Wei Chang, and Jina Suh. 2016. The value of semantic parse labeling for knowledge base question answering. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 201–206, Berlin, Germany. Association for Computational Linguistics.
Tao Yu, Zifan Li, Zilin Zhang, Rui Zhang, and Dragomir Radev. 2018. TypeSQL: Knowledge-based type-aware neural text-to-SQL generation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 588-594, New Orleans, Louisiana. Association for Computational Linguistics.
Changchang Zeng, Shaobo Li, Qin Li, Jie Hu, and Jianjun Hu. 2020. A survey on machine reading comprehension: Tasks, evaluation metrics and benchmark datasets.
Xingyao Zhang, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen, and Daxin Jiang. 2020. A graph representation of semi-structured data for web question answering. In Proceedings of the 28th International Conference on Computational Linguistics, pages 51–61, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Yanbin Zhao, Lu Chen, Zhi Chen, Ruisheng Cao, Su Zhu, and Kai Yu. 2020. Line graph enhanced AMR-to-text generation with mix-order graph attention networks. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 732-741, Online. Association for Computational Linguistics.
Su Zhu, Jieyu Li, Lu Chen, and Kai Yu. 2020. Efficient context and schema fusion networks for multi-domain dialogue state tracking. In *Findings of the Association for Computational Linguistics: EMNLP* 2020, pages 766-781, Online. Association for Computational Linguistics.
A Detail Setup
To train the model, we use AdamW (Loshchilov and Hutter, 2019) with a linear schedule as our optimizer. As for the learning rate, we search for the
best learning rate between 1e-6 and 5e-5. Finally, TIE is trained and evaluated on four Nvidia A10 Graphics Cards with batch size 32 for two epochs. Moreover, for BASE size models (12 heads in total), we use DOM Trees to generate the mask matrix for 4 attention heads and each of the 4 NPR graphs for 2 attention heads. And for LARGE size models (16 heads in total), we add one more attention head using each of the 4 NPR graphs.
B Additional Case Study
Figure 7, 8, and 9 shows the typical examples of the QA pairs in KV, Table, and Compare websites, respectively.
Through detailed analysis, we found that TIE can better capture the long-range relations which have obvious spacial relations, such as header-cell and entity-attribute (see Fig. 7 Q3, Fig. 8 Q1, and Fig. 9 Q2). On the other hand, as TIE focuses more on tag-level structure understanding, its ability to understand token-level semantics may be weaker, which leads to some of the TIE's wrong predictions (see Fig. 7 Q1, Fig. 8 Q2, and Fig. 9 Q3). In addition, TIE has a better awareness of tag boundaries, which has been proven useful when answering questions with blurry boundaries (see Fig. 7 Q2, Q3, and Fig. 9 Q1).
Q1: Who is the developer of
the game?
Q2: How long is this movie?
93 min.
93 min. Action / War Trailer Watchlist 2020 NR 93 min.
Vehicle Highlights
Fuel Economy: 13 mpg City 22 mpg Hwy Engine: 4.0 L Twin turbo Hybrid V-8, 563 HP
Transmission: Automatic
View More Features and Specifications
Basic Warranty: 4 Years / 50,000 Miles
Drivetrain Warranty: 4 Years / 50,000 Miles
Roadside Assistance: 4 Years / Unlimited Miles
Hybrid Component: 8 Years / 100,000 Miles
A vehicle's warranty can significant impact your maintenance costs after you drive off the dealer's lot, and it's important to understand the different parts. Typically, a new car warranty includes a Basic warranty, which covers everything except the wear items such as brakes and tires; and a Drivetrain warranty, that covers all the parts that make the car move, such as the engine and transmission
Q3: How much fuel economy is there for city?
A3:
13 mpg City
13 mpg City;
13 mpg City, 22  
mpg Hwy Engine: 4.0
Figure 7: Examples of the results from  $KV$  type websites in the development set.
TIE(MarkupLM)
Q1: What's the “PDEF” of this player in 2019?
Q2: Who holds the "HT" of 7-0?
Figure 8: Examples of the results from Table type websites in the development set.
Q1: Which engine does the Turbo SE-hybrid have?
Lowest-Priced
Base Style
20 MPG
Combined Fuel Economy
Seating
335 @ 5300 RPM
V6.Turbo,3.0Liter
E-hybrid
21 MPG | 41 Mpge
455 @ 5300 RPM
Horsepow
V6, Turbo, Hybrid, 3.0
434 @ 5700 RPM
V6. Twin Turbo, 2.9 Liter
17 MPG
541 @ 5750 RPM
V8, Twin Turbo, 4.0 Liter
Turbo S E-hybrid
18 MPG | 39 Mpge
670 @ 5750 RPM
V8, Hybrid, Twin Turbo
4.0 Liter
Q2: The writer of the book "Minecraft Guide to Farming" is?
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Fine,
Fantasticly Great
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Kate Pankhurst
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Q3: When was the job offer "Azure CLOUD Subject Matter
Expert(Databricks) Leading MNC" posted?
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Figure 9: Examples of the results from Compare type websites in the development set.