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Timo Denk · Ioannis Androutsopoulos · Oleg Bakhteev · Mohamed Kane · Petar Stojanov · Seunghyun Park · Bharat Mamidibathula · Kostiantyn Liepieshov · Johannes Höhne · Song Feng · Zikri Bayraktar · Kehinde Aruleba · ALEKSANDR OGALTSOV · Rita Kuznetsova · Paul Bennett · Saghar Hosseini · Kshtij Fadnis · Luis Lastras · Mehrdad Jabbarzadeh Gangeh · Christian Reisswig · Emad Elwany · Ilias Chalkidis · Jonathan DeGange · Kaixuan Zhang · Luke de Oliveira · Muhammed Koçyiğit · Haoyu Dong · Vera Liao · Wonseok Hwang

Sat Dec 14 12:05 PM -- 01:30 PM (PST) @
Event URL: https://sites.google.com/view/di2019/accepted-papers »

Papers presented as re follows: “Repurposing Decoder-Transformer Language Models for Abstractive Summarization” by Luke de Oliveira, and Alfredo Láinez Rodrigo. “From Stroke to Finite Automata: An Offline Recognition Approach”, by Kehinde Aruleba. “Post-OCR parsing: building simple and robust parser via BIO tagging”, by Wonseok Hwang, Seonghyeon Kim, Minjoon Seo, Jinyeong Yim, Seunghyun Park, Sungrae Park, Junyeop Lee, Bado Lee, Hwalsuk Lee. “CrossLang: the system of cross-lingual plagiarism detection”, by Oleg Bakhteev, Alexandr Ogaltsov, Andrey Khazov, Kamil Safin, Rita Kuznetsova. “BERTgrid: Contextualized Embedding for 2D Document Representation and Understanding”, Timo I. Denk, Christian Reisswig. “Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection” by Christian Reisswig, Anoop R Katti, Marco Spinaci, Johannes Höhne. “SVDocNet: Spatially Variant U-Net for Blind Document Deblurring”, by Bharat Mamidibathula, Prabir Kumar Biswas. “Semantic Structure Extraction for Spreadsheet Tables with a Multi-task Learning Architecture", by Haoyu Dong, Shijie Liu, Zhouyu Fu, Shi Han, Dongmei Zhang. “Document Enhancement System Using Auto-encoders", by Mehrdad J. Gangeh, Sunil R. Tiyyagura, Sridhar V. Dasaratha, Hamid Motahari, Nigel P. Duffy. “CORD: A Consolidated Receipt Dataset for Post-OCR Parsing”, by Seunghyun Park, Seung Shin, Bado Lee, Junyeop Lee, Jaeheung Surh, Minjoon Seo, Hwalsuk Lee. “On recognition of Cyrillic Text”, by Kostiantyn Liepieshov, Oles Dobosevych. “Representation Learning in Geology and GilBERT”, by Zikri Bayraktar, Hedi Driss, Marie Lefranc. “Neural Contract Element Extraction Revisited”, by Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, Ion Androutsopoulos. “Doc2Dial: a Framework for Dialogue Composition Grounded in Business Documents”, by Song Feng, Kshitij Fadni, Q. Vera Liao, Luis A. Lastras. “On Domain Transfer When Predicting Intent in Text”, by Petar Stojanov, Ahmed Hassan Awadallah, Paul Bennett, Saghar Hosseini. “BERT Goes to Law School: Quantifying the Competitive Advantage of Access to Large Legal Corpora in Contract Understanding", by Emad Elwany, Dave Moore, Gaurav Oberoi. “Information Extraction from Text Regions with Complex Structure”, by Kaixuan Zhang, Zejiang Shen, Jie Zhou, Melissa Dell. “DeepErase: Unsupervised Ink Artifact Removal in Document Text Images”, Yike Qi, W. Ronny Huang, Qianqian Li, Jonathan L. Degange. “Towards Neural Similarity Evaluator” , Hassan Kané, Yusuf Kocyigit, Pelkins Ajanoh, Ali Abdalla, Mohamed Coulibali.

Author Information

Timo Denk (DHBW Karlsruhe)
Ioannis Androutsopoulos (Athens University of Economics and Business)
Oleg Bakhteev (Moscow Institute of Physics and Technology)
Mohamed Kane (WL)
Petar Stojanov (Carnegie Mellon University)
Seunghyun Park (Naver)
Bharat Mamidibathula (Indian Institute of Technology, Kharagpur)
Kostiantyn Liepieshov (Ukrainian Catholic University)
Johannes Höhne (SAP SE)
Song Feng (IBM Research)
Zikri Bayraktar (Schlumberger Doll Research)

Zikri Bayraktar is a senior research scientist and machine learning lead at the Schlumberger-Doll Research Center in Cambridge, MA focusing on artificial intelligence and machine learning based solutions to engineering problems at various scales ranging from borehole to seismic. He received his PhD in electrical engineering and a PhD minor in computational science in 2011 from Pennsylvania State University. Dr. Bayraktar is also an alumnus of the Schreyer Honors College Integrated Undergraduates/Graduated program at Penn State with MSc and BSc degrees in electrical engineering. After graduation, he completed a year-long post-doctoral assignment at Penn State and then joined IBM Semiconductor R&D Center in 2012 as an advisory engineer focusing on production of IBM server microchips. Since 2014, Dr. Bayraktar is with Schlumberger initially in computational electromagnetic group and currently in automated geology department. Dr. Bayraktar has published more than 45 journal and conference papers with multiple patent submissions focusing on machine learning applications in oil and gas industry. He is a member of the IEEE, Society of Petroleum Engineers (SPE), and Society of Petrophysicists and Wirelog Analysts (SPWLA). Dr. Bayraktar is also serving as one of the 2020 Distinguished Speakers of the SPWLA.

Kehinde Aruleba (University of the Witwatersrand)
ALEKSANDR OGALTSOV (Higher School of Economics, Moscow)
Rita Kuznetsova (Moscow Institute of Physics and Technology, Antiplagiat Company)
Paul Bennett (Microsoft Research)
Saghar Hosseini
Kshtij Fadnis (IBM Research)
Luis Lastras (IBM Research AI)
Mehrdad Jabbarzadeh Gangeh (Ernst & Young)

Mehrdad J. Gangeh received his Ph.D. in Electrical and Computer Engineering from University of Waterloo, Canada, in 2013. Mehrdad recently joined AI Lab at EY as Senior AI Scientist and prior to EY, he was a Research Scientist jointly at the Dept. of Medical Biophysics, University of Toronto and the Dept. of Radiation Oncology, Sunnybrook Health Sciences Center, Canada. His research interests are on deep learning, multiview learning, dictionary learning and sparse representation, and kernel methods, with the applications to computer vision, medical imaging, natural language processing, text analytics, pattern recognition, big data analytics, and data mining. He is Associate Editor of IEEE Trans. on Medical Imaging (TMI) and Adjunct Professor at the Dept. of System Design Engineering, University of Waterloo.

Christian Reisswig (SAP SE)
Emad Elwany (Lexion)
Ilias Chalkidis (NCSR "Demokritos")
Jonathan DeGange (Ernst & Young)
Kaixuan Zhang (Harvard University)
Luke de Oliveira (Twilio AI)

Luke de Oliveira is the Technical Lead for language understanding and machine learning at Twilio, Inc., where he is responsible for the tools, team, and platform to create the next-generation contact center. Luke was most recently CEO & founder at Vai Technologies, which was acquired by Twilio to start the language understanding and machine learning team. He also actively publishes work in both NLP and scientific applications of deep learning, and is a visiting researcher at Lawrence Berkeley National Laboratory (LBNL). Luke also serves as a technology and product advisor to numerous startups.

Muhammed Koçyiğit (Bogazici University)
Haoyu Dong (Microsoft)
Vera Liao (IBM Research AI)
Wonseok Hwang (Naver)

Interested in NLP, application of machine learning (deep learning), and mathematical, computational, and probabilistic modeling of scientific and industrial data. I have many top-tier AI conference publication record (EMNLP, Findings of ACL, NeurIPS, AAAI, and ECCV). [CV](https://docs.google.com/document/d/1RSKLnjg4tUTwRNbIIj8WvkhDQNFUVcWXdSy4Juu2jU4/edit)

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