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Research"}, {"self_ref": "#/texts/4", "parent": {"cref": "#/groups/0"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 1, "bbox": {"l": 222.966, "t": 563.191, "r": 392.39, "b": 555.722, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 36]}], "orig": "{mly,ahn,nli,cau,taa}@zurich.ibm.com", "text": "{mly,ahn,nli,cau,taa}@zurich.ibm.com"}, {"self_ref": "#/texts/5", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 1, "bbox": {"l": 163.111, "t": 521.699, "r": 206.636, "b": 513.773, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 9]}], "orig": "Abstract.", "text": "Abstract."}, {"self_ref": "#/texts/6", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 1, "bbox": {"l": 163.111, "t": 313.306, "r": 211.942, "b": 305.38, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 9]}], "orig": "Keywords:", "text": "Keywords:"}, {"self_ref": "#/texts/7", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 1, "bbox": {"l": 134.765, "t": 269.88, "r": 141.489, "b": 259.312, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "1", "text": "1", "level": 1}, {"self_ref": "#/texts/8", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 1, "bbox": {"l": 134.765, "t": 243.71299999999997, "r": 480.594, "b": 234.91599999999994, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 79]}], "orig": "Tables are ubiquitous in documents such as scientific papers, patents, reports,", "text": "Tables are ubiquitous in documents such as scientific papers, patents, reports,"}, {"self_ref": "#/texts/9", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 1, "bbox": {"l": 149.708, "t": 159.85199999999998, "r": 480.589, "b": 151.05500000000006, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 74]}], "orig": "In modern document understanding systems [1,15], table extraction is typi-", "text": "In modern document understanding systems [1,15], table extraction is typi-"}, {"self_ref": "#/texts/10", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 2, "bbox": {"l": 134.765, "t": 700.507, "r": 139.372, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "2", "text": "2"}, {"self_ref": "#/texts/11", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 2, "bbox": {"l": 167.813, "t": 700.507, "r": 231.722, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/12", "parent": {"cref": "#/pictures/0"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 2, "bbox": {"l": 134.765, "t": 665.666, "r": 162.644, "b": 657.74, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 1.", "text": "Fig. 1."}, {"self_ref": "#/texts/13", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 2, "bbox": {"l": 134.765, "t": 339.686, "r": 161.329, "b": 330.889, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 6]}], "orig": "today,", "text": "today,"}, {"self_ref": "#/texts/14", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 2, "bbox": {"l": 149.709, "t": 267.44900000000007, "r": 187.471, "b": 258.65200000000004, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 8]}], "orig": "Recently", "text": "Recently"}, {"self_ref": "#/texts/15", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 3, "bbox": {"l": 194.478, "t": 700.507, "r": 447.543, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 60]}], "orig": "Optimized Table Tokenization for Table Structure Recognition", "text": "Optimized Table Tokenization for Table Structure Recognition"}, {"self_ref": "#/texts/16", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 3, "bbox": {"l": 475.984, "t": 700.507, "r": 480.591, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "3", "text": "3"}, {"self_ref": "#/texts/17", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 3, "bbox": {"l": 149.709, "t": 673.066, "r": 480.592, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 74]}], "orig": "While the majority of research in TSR is currently focused on the develop-", "text": "While the majority of research in TSR is currently focused on the develop-"}, {"self_ref": "#/texts/18", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 3, "bbox": {"l": 149.709, "t": 577.164, "r": 480.594, "b": 568.367, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 78]}], "orig": "The main contribution of this paper is the introduction of a new optimised ta-", "text": "The main contribution of this paper is the introduction of a new optimised ta-"}, {"self_ref": "#/texts/19", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 3, "bbox": {"l": 149.709, "t": 457.352, "r": 480.588, "b": 448.555, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 76]}], "orig": "The paper is structured as follows. In section 2, we give an overview of the", "text": "The paper is structured as follows. In section 2, we give an overview of the"}, {"self_ref": "#/texts/20", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 3, "bbox": {"l": 134.765, "t": 329.912, "r": 141.489, "b": 319.344, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "2", "text": "2", "level": 1}, {"self_ref": "#/texts/21", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 3, "bbox": {"l": 134.765, "t": 303.314, "r": 480.591, "b": 294.517, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 80]}], "orig": "Approaches to formalize the logical structure and layout of tables in electronic", "text": "Approaches to formalize the logical structure and layout of tables in electronic"}, {"self_ref": "#/texts/22", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 4, "bbox": {"l": 134.765, "t": 700.507, "r": 139.372, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "4", "text": "4"}, {"self_ref": "#/texts/23", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 4, "bbox": {"l": 167.813, "t": 700.507, "r": 231.722, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/24", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 4, "bbox": {"l": 134.765, "t": 673.066, "r": 480.594, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 81]}], "orig": "Other work [20] aims at predicting a grid for each table and deciding which cells", "text": "Other work [20] aims at predicting a grid for each table and deciding which cells"}, {"self_ref": "#/texts/25", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 4, "bbox": {"l": 149.709, "t": 529.343, "r": 199.213, "b": 520.546, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 10]}], "orig": "Within the", "text": "Within the"}, {"self_ref": "#/texts/26", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 4, "bbox": {"l": 149.709, "t": 301.934, "r": 480.594, "b": 293.137, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 75]}], "orig": "Im2Seq approaches have shown to be well-suited for the TSR task and allow a", "text": "Im2Seq approaches have shown to be well-suited for the TSR task and allow a"}, {"self_ref": "#/texts/27", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 4, "bbox": {"l": 134.765, "t": 186.45000000000005, "r": 141.489, "b": 175.88200000000006, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "3", "text": "3", "level": 1}, {"self_ref": "#/texts/28", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 4, "bbox": {"l": 134.765, "t": 159.85199999999998, "r": 480.591, "b": 151.05500000000006, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 73]}], "orig": "All known Im2Seq based models for TSR fundamentally work in similar ways.", "text": "All known Im2Seq based models for TSR fundamentally work in similar ways."}, {"self_ref": "#/texts/29", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 5, "bbox": {"l": 194.478, "t": 700.507, "r": 447.543, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 60]}], "orig": "Optimized Table Tokenization for Table Structure Recognition", "text": "Optimized Table Tokenization for Table Structure Recognition"}, {"self_ref": "#/texts/30", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 5, "bbox": {"l": 475.984, "t": 700.507, "r": 480.591, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "5", "text": "5"}, {"self_ref": "#/texts/31", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 5, "bbox": {"l": 134.765, "t": 673.066, "r": 480.586, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 77]}], "orig": "ulary and can be interpreted as a table structure. For example, with the HTML", "text": "ulary and can be interpreted as a table structure. For example, with the HTML"}, {"self_ref": "#/texts/32", "parent": {"cref": "#/pictures/1"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 5, "bbox": {"l": 145.607, "t": 570.921, "r": 173.486, "b": 562.995, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 2.", "text": "Fig. 2."}, {"self_ref": "#/texts/33", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 5, "bbox": {"l": 149.709, "t": 423.793, "r": 480.593, "b": 414.996, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 71]}], "orig": "Obviously, HTML and other general-purpose markup languages were not de-", "text": "Obviously, HTML and other general-purpose markup languages were not de-"}, {"self_ref": "#/texts/34", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 5, "bbox": {"l": 149.709, "t": 255.957, "r": 480.593, "b": 247.15999999999997, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 76]}], "orig": "Additionally, it would be desirable if the representation would easily allow", "text": "Additionally, it would be desirable if the representation would easily allow"}, {"self_ref": "#/texts/35", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 5, "bbox": {"l": 149.709, "t": 207.673, "r": 480.593, "b": 198.87599999999998, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 74]}], "orig": "In a valid HTML table, the token sequence must describe a 2D grid of table", "text": "In a valid HTML table, the token sequence must describe a 2D grid of table"}, {"self_ref": "#/texts/36", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 700.507, "r": 139.372, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "6", "text": "6"}, {"self_ref": "#/texts/37", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 6, "bbox": {"l": 167.813, "t": 700.507, "r": 231.722, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/38", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 673.066, "r": 480.595, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 78]}], "orig": "generation. Implicitly, this also means that Im2Seq models need to learn these", "text": "generation. Implicitly, this also means that Im2Seq models need to learn these"}, {"self_ref": "#/texts/39", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 149.709, "t": 648.517, "r": 480.59, "b": 639.72, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 76]}], "orig": "In practice, we observe two major issues with prediction quality when train-", "text": "In practice, we observe two major issues with prediction quality when train-"}, {"self_ref": "#/texts/40", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 471.369, "r": 141.489, "b": 460.801, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "4", "text": "4", "level": 1}, {"self_ref": "#/texts/41", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 442.883, "r": 480.591, "b": 434.086, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 76]}], "orig": "To mitigate the issues with HTML in Im2Seq-based TSR models laid out before,", "text": "To mitigate the issues with HTML in Im2Seq-based TSR models laid out before,"}, {"self_ref": "#/texts/42", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 326.128, "r": 149.402, "b": 317.321, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "4.1", "text": "4.1", "level": 1}, {"self_ref": "#/texts/43", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 134.765, "t": 303.002, "r": 480.589, "b": 294.205, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 80]}], "orig": "In Figure 3, we illustrate how the OTSL is defined. In essence, the OTSL defines", "text": "In Figure 3, we illustrate how the OTSL is defined. In essence, the OTSL defines"}, {"self_ref": "#/texts/44", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 149.709, "t": 266.49800000000005, "r": 409.311, "b": 257.701, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 57]}], "orig": "The OTSL vocabulary is comprised of the following tokens:", "text": "The OTSL vocabulary is comprised of the following tokens:"}, {"self_ref": "#/texts/45", "parent": {"cref": "#/groups/1"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 6, "bbox": {"l": 140.993, "t": 244.02999999999997, "r": 146.72, "b": 235.22299999999996, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "-", "text": "-", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/46", "parent": {"cref": "#/groups/1"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 6, "bbox": {"l": 140.993, "t": 231.437, "r": 146.72, "b": 222.63, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "-", "text": "-", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/47", "parent": {"cref": "#/groups/1"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 6, "bbox": {"l": 140.993, "t": 206.88800000000003, "r": 146.72, "b": 198.08100000000002, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "-", "text": "-", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/48", "parent": {"cref": "#/groups/1"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 6, "bbox": {"l": 140.993, "t": 182.34000000000003, "r": 146.72, "b": 173.53300000000002, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "-", "text": "-", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/49", "parent": {"cref": "#/groups/1"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 6, "bbox": {"l": 140.993, "t": 169.74599999999998, "r": 146.72, "b": 160.93899999999996, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "-", "text": "-", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/50", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 6, "bbox": {"l": 149.709, "t": 147.89699999999993, "r": 480.593, "b": 139.10000000000002, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 79]}], "orig": "A notable attribute of OTSL is that it has the capability of achieving lossless", "text": "A notable attribute of OTSL is that it has the capability of achieving lossless"}, {"self_ref": "#/texts/51", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 7, "bbox": {"l": 194.478, "t": 700.507, "r": 447.543, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 60]}], "orig": "Optimized Table Tokenization for Table Structure Recognition", "text": "Optimized Table Tokenization for Table Structure Recognition"}, {"self_ref": "#/texts/52", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 7, "bbox": {"l": 475.984, "t": 700.507, "r": 480.591, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "7", "text": "7"}, {"self_ref": "#/texts/53", "parent": {"cref": "#/pictures/2"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 7, "bbox": {"l": 134.765, "t": 666.201, "r": 162.644, "b": 658.275, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 3.", "text": "Fig. 3."}, {"self_ref": "#/texts/54", "parent": {"cref": "#/pictures/2"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 334.511, "t": 519.112, "r": 426.599, "b": 513.0, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 33]}], "orig": "4 - 2d merges: \"C\", \"L\", \"U\", \"X\"", "text": "4 - 2d merges: \"C\", \"L\", \"U\", \"X\"", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/55", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 7, "bbox": {"l": 134.765, "t": 486.704, "r": 149.402, "b": 477.897, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "4.2", "text": "4.2", "level": 1}, {"self_ref": "#/texts/56", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 7, "bbox": {"l": 134.765, "t": 466.752, "r": 363.796, "b": 457.955, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 51]}], "orig": "The OTSL representation follows these syntax rules:", "text": "The OTSL representation follows these syntax rules:"}, {"self_ref": "#/texts/57", "parent": {"cref": "#/groups/2"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 444.819, "r": 146.72, "b": 436.022, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "1.", "text": "1.", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/58", "parent": {"cref": "#/groups/2"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 420.905, "r": 146.72, "b": 412.108, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "2.", "text": "2.", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/59", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 396.992, "r": 146.72, "b": 388.195, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "3.", "text": "3.", "level": 1}, {"self_ref": "#/texts/60", "parent": {"cref": "#/groups/3"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 349.164, "r": 146.72, "b": 340.367, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "4.", "text": "4.", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/61", "parent": {"cref": "#/groups/3"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 337.206, "r": 146.72, "b": 328.409, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "5.", "text": "5.", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/62", "parent": {"cref": "#/groups/3"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 138.973, "t": 313.293, "r": 146.72, "b": 304.496, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "6.", "text": "6.", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/63", "parent": {"cref": "#/groups/3"}, "children": [], "content_layer": "body", "label": "list_item", "prov": [{"page_no": 7, "bbox": {"l": 151.701, "t": 385.033, "r": 480.592, "b": 376.236, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 74]}], "orig": "The left neighbour of an \"X\" cell must be either another \"X\" cell or a \"U\"", "text": "The left neighbour of an \"X\" cell must be either another \"X\" cell or a \"U\"", "enumerated": false, "marker": "-"}, {"self_ref": "#/texts/64", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 7, "bbox": {"l": 149.709, "t": 279.4069999999999, "r": 480.596, "b": 270.61, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 75]}], "orig": "The application of these rules gives OTSL a set of unique properties. First", "text": "The application of these rules gives OTSL a set of unique properties. First"}, {"self_ref": "#/texts/65", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 7, "bbox": {"l": 149.709, "t": 147.89699999999993, "r": 480.592, "b": 139.10000000000002, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 75]}], "orig": "These characteristics can be easily learned by sequence generator networks,", "text": "These characteristics can be easily learned by sequence generator networks,"}, {"self_ref": "#/texts/66", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 700.507, "r": 139.372, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "8", "text": "8"}, {"self_ref": "#/texts/67", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 8, "bbox": {"l": 167.813, "t": 700.507, "r": 231.722, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/68", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 673.066, "r": 480.589, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 78]}], "orig": "reduces significantly the column drift seen in the HTML based models (see Fig-", "text": "reduces significantly the column drift seen in the HTML based models (see Fig-"}, {"self_ref": "#/texts/69", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 630.443, "r": 149.402, "b": 621.636, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "4.3", "text": "4.3", "level": 1}, {"self_ref": "#/texts/70", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 609.718, "r": 480.596, "b": 600.921, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 79]}], "orig": "The design of OTSL allows to validate a table structure easily on an unfinished", "text": "The design of OTSL allows to validate a table structure easily on an unfinished"}, {"self_ref": "#/texts/71", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 470.836, "r": 141.489, "b": 460.268, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "5", "text": "5", "level": 1}, {"self_ref": "#/texts/72", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 444.75, "r": 480.594, "b": 435.953, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 77]}], "orig": "To evaluate the impact of OTSL on prediction accuracy and inference times, we", "text": "To evaluate the impact of OTSL on prediction accuracy and inference times, we"}, {"self_ref": "#/texts/73", "parent": {"cref": "#/pictures/3"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 8, "bbox": {"l": 134.765, "t": 307.352, "r": 162.644, "b": 299.426, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 4.", "text": "Fig. 4."}, {"self_ref": "#/texts/74", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 8, "bbox": {"l": 149.709, "t": 171.80700000000002, "r": 480.588, "b": 163.01, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 71]}], "orig": "We rely on standard metrics such as Tree Edit Distance score (TEDs) for", "text": "We rely on standard metrics such as Tree Edit Distance score (TEDs) for"}, {"self_ref": "#/texts/75", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 9, "bbox": {"l": 194.478, "t": 700.507, "r": 447.543, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 60]}], "orig": "Optimized Table Tokenization for Table Structure Recognition", "text": "Optimized Table Tokenization for Table Structure Recognition"}, {"self_ref": "#/texts/76", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 9, "bbox": {"l": 475.984, "t": 700.507, "r": 480.591, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "9", "text": "9"}, {"self_ref": "#/texts/77", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 673.066, "r": 480.594, "b": 664.269, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 76]}], "orig": "order to compute the TED score. Inference timing results for all experiments", "text": "order to compute the TED score. Inference timing results for all experiments"}, {"self_ref": "#/texts/78", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 622.814, "r": 149.402, "b": 614.007, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "5.1", "text": "5.1", "level": 1}, {"self_ref": "#/texts/79", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 606.414, "r": 480.592, "b": 597.617, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 73]}], "orig": "We have chosen the PubTabNet data set to perform HPO, since it includes a", "text": "We have chosen the PubTabNet data set to perform HPO, since it includes a"}, {"self_ref": "#/texts/80", "parent": {"cref": "#/tables/0"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 516.928, "r": 160.118, "b": 509.002, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 5]}], "orig": "Table", "text": "Table"}, {"self_ref": "#/texts/81", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 283.848, "r": 149.402, "b": 275.04099999999994, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "5.2", "text": "5.2", "level": 1}, {"self_ref": "#/texts/82", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 9, "bbox": {"l": 134.765, "t": 267.44900000000007, "r": 480.591, "b": 258.65200000000004, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 77]}], "orig": "We picked the model parameter configuration that produced the best prediction", "text": "We picked the model parameter configuration that produced the best prediction"}, {"self_ref": "#/texts/83", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 9, "bbox": {"l": 149.709, "t": 171.80700000000002, "r": 205.597, "b": 163.01, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 13]}], "orig": "Additionally,", "text": "Additionally,"}, {"self_ref": "#/texts/84", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 10, "bbox": {"l": 134.765, "t": 700.507, "r": 143.979, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "10", "text": "10"}, {"self_ref": "#/texts/85", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 10, "bbox": {"l": 167.821, "t": 700.507, "r": 231.72, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/86", "parent": {"cref": "#/tables/1"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 10, "bbox": {"l": 134.765, "t": 676.164, "r": 173.094, "b": 668.238, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 8]}], "orig": "Table 2.", "text": "Table 2."}, {"self_ref": "#/texts/87", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 10, "bbox": {"l": 134.765, "t": 503.085, "r": 149.402, "b": 494.278, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 3]}], "orig": "5.3", "text": "5.3", "level": 1}, {"self_ref": "#/texts/88", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 10, "bbox": {"l": 134.765, "t": 482.139, "r": 189.59, "b": 473.342, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 13]}], "orig": "To illustrate", "text": "To illustrate"}, {"self_ref": "#/texts/89", "parent": {"cref": "#/pictures/4"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 10, "bbox": {"l": 134.765, "t": 394.41, "r": 162.644, "b": 386.484, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 5.", "text": "Fig. 5."}, {"self_ref": "#/texts/90", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 11, "bbox": {"l": 194.478, "t": 700.507, "r": 447.543, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 60]}], "orig": "Optimized Table Tokenization for Table Structure Recognition", "text": "Optimized Table Tokenization for Table Structure Recognition"}, {"self_ref": "#/texts/91", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 11, "bbox": {"l": 471.376, "t": 700.507, "r": 480.59, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "11", "text": "11"}, {"self_ref": "#/texts/92", "parent": {"cref": "#/pictures/5"}, "children": [], "content_layer": "body", "label": "caption", "prov": [{"page_no": 11, "bbox": {"l": 134.765, "t": 666.201, "r": 162.644, "b": 658.275, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 7]}], "orig": "Fig. 6.", "text": "Fig. 6."}, {"self_ref": "#/texts/93", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 12, "bbox": {"l": 134.765, "t": 700.507, "r": 143.979, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 2]}], "orig": "12", "text": "12"}, {"self_ref": "#/texts/94", "parent": {"cref": "#/body"}, "children": [], "content_layer": "furniture", "label": "page_header", "prov": [{"page_no": 12, "bbox": {"l": 167.821, "t": 700.507, "r": 231.72, "b": 689.218, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 16]}], "orig": "M. Lysak, et al.", "text": "M. Lysak, et al."}, {"self_ref": "#/texts/95", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "section_header", "prov": [{"page_no": 12, "bbox": {"l": 134.765, "t": 674.451, "r": 141.489, "b": 663.883, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 1]}], "orig": "6", "text": "6", "level": 1}, {"self_ref": "#/texts/96", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 12, "bbox": {"l": 134.765, "t": 645.136, "r": 480.595, "b": 636.339, "coord_origin": "BOTTOMLEFT"}, "charspan": [0, 77]}], "orig": "We demonstrated that representing tables in HTML for the task of table struc-", "text": "We demonstrated that representing tables in HTML for the task of table struc-"}, {"self_ref": "#/texts/97", "parent": {"cref": "#/body"}, "children": [], "content_layer": "body", "label": "text", "prov": [{"page_no": 12, "bbox": {"l": 149.709, "t": 584.556, "r": 480.593, "b": 575.759, "coord_origin": "BOTTOMLEFT"}, 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