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| "paper_id": "2021", | |
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| "date_generated": "2023-01-19T14:47:21.202272Z" | |
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| "title": "Message from the Workshop Chairs", | |
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| "abstract": "Developing intelligent systems which can produce concise, fluent, and accurate summaries has been a long-standing goal in natural language processing. The aim of this workshop is to provide a research forum for cross-fertilization of ideas towards this goal. We seek to bring together researchers from a diverse range of fields (e.g., summarization, language generation, cognitive and psycholinguistics) for discussions on key issues related to automatic summarization. This includes discussion on novel paradigms/frameworks, multilingual and cross-lingual setups, shared tasks of interest, information integration and presentation, new evaluation protocols, applied research and applications, and possible future research foci. The workshop aims to pave the way towards building a cohesive research community, accelerating knowledge diffusion, developing new tools, datasets, and resources that are in line with the needs of academia, industry, and government. This is the third edition of the workshop, following our previous workshops at EMNLP 2017 and EMNLP 2019. The workshop", | |
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| "text": "Developing intelligent systems which can produce concise, fluent, and accurate summaries has been a long-standing goal in natural language processing. The aim of this workshop is to provide a research forum for cross-fertilization of ideas towards this goal. We seek to bring together researchers from a diverse range of fields (e.g., summarization, language generation, cognitive and psycholinguistics) for discussions on key issues related to automatic summarization. This includes discussion on novel paradigms/frameworks, multilingual and cross-lingual setups, shared tasks of interest, information integration and presentation, new evaluation protocols, applied research and applications, and possible future research foci. The workshop aims to pave the way towards building a cohesive research community, accelerating knowledge diffusion, developing new tools, datasets, and resources that are in line with the needs of academia, industry, and government. This is the third edition of the workshop, following our previous workshops at EMNLP 2017 and EMNLP 2019. The workshop", | |
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| "section": "Abstract", | |
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| "text": "Shashi Narayan (Google) Asli Celikyilmaz (Facebook AI Research) Sebastian Gehrmann (Google) ", | |
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| "section": "Invited Speakers", | |
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| "back_matter": [ | |
| { | |
| "text": "A New Dataset and Efficient Baselines for Document-level Text Simplification in German Annette Rios, Nicolas Spring, Tannon Kew, Marek Kostrzewa, Andreas S\u00e4uberli, Mathias M\u00fcller and Sarah Ebling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 ", | |
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| "start": 95, | |
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| "text": "Rios,", | |
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| "start": 101, | |
| "end": 116, | |
| "text": "Nicolas Spring,", | |
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| "start": 117, | |
| "end": 128, | |
| "text": "Tannon Kew,", | |
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| "start": 129, | |
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| "text": "Marek Kostrzewa,", | |
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| "text": "Andreas S\u00e4uberli,", | |
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| "text": "Mathias M\u00fcller and Sarah Ebling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152", | |
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| "raw_text": "Modeling Endorsement for Multi-Document Abstractive Summarization Logan Lebanoff, Bingqing Wang, Zhe Feng and Fei Liu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Documents Nishant Yadav, Matteo Brucato, Anna Fariha, Oscar Youngquist, Julian Killingback, Alexandra Meliou and Peter Haas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt and Nazli Goharian . . . . . . . . . . . . . . 142", | |
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| "title": "Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings Nicole Beckage", | |
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| "raw_text": "Conference Program 9:00-10:30 Morning Session I 9:00-9:10 Open remarks NewSum Organizers 9:10-10:00 Keynote I Sashi Narayan (Google) 10:00-10:10 Sentence-level Planning for Especially Abstractive Summarization Andreas Marfurt and James Henderson 10:10-10:20 Template-aware Attention Model for Earnings Call Report Generation Yangchen Huang, Prashant K. Dhingra and Seyed Danial Mohseni Taheri 10:20-10:25 Knowledge and Keywords Augmented Abstractive Sentence Summarization Shuo Guan 10:25-10:30 Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Sum- marization Khalil Mrini, Can Liu and Markus Dreyer 10:30-11:00 Coffee break I 11:00-12:00 Morning session II 11:00-11:50 Keynote II Sebastian Gehrmann (Google) 11:50-12:00 A Novel Wikipedia based Dataset for Monolingual and Cross-Lingual Summariza- tion Mehwish Fatima and Michael Strube 12:00-13:00 Lunch break November 10 (continued) 13:00-14:30 Afternoon session I 13:00-13:50 Keynote III Asli Celikyilmaz (Facebook AI Research) 13:50-13:55 Evaluation of Summarization Systems across Gender, Age, and Race Anna J\u00f8rgensen and Anders S\u00f8gaard 13:55-14:00 Evaluation of Abstractive Summarisation Models with Machine Translation in De- liberative Processes Miguel Arana-Catania, Rob Procter, Yulan He and Maria Liakata 14:00-14:10 Capturing Speaker Incorrectness: Speaker-Focused Post-Correction for Abstractive Dialogue Summarization Dongyub Lee, Jungwoo Lim, Taesun Whang, chanhee lee, Seungwoo Cho, Mingun Park and Heuiseok Lim 14:10-14:20 Measuring Similarity of Opinion-bearing Sentences Wenyi Tay, Xiuzhen Zhang, Stephen Wan and Sarvnaz Karimi 14:20-14:30 EASE: Extractive-Abstractive Summarization End-to-End using the Information Bottleneck Principle Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta and Marjan Ghazvininejad 14:30-15:00 Coffee break 15:00-16:15 Afternoon session II 15:00-15:10 Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings Nicole Beckage, Shachi H Kumar, Saurav Sahay and Ramesh Manuvinakurike 15:10-15:20 Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets Don Tuggener, Margot Mieskes, Jan Deriu and Mark Cieliebak 15:20-15:30 Modeling Endorsement for Multi-Document Abstractive Summarization Logan Lebanoff, Bingqing Wang, Zhe Feng and Fei Liu x November 10 (continued) 15:30-15:35 SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Docu- ments Nishant Yadav, Matteo Brucato, Anna Fariha, Oscar Youngquist, Julian Killingback, Alexandra Meliou and Peter Haas 15:35-16:15 EMNLP finding papers -Summarization 16:15-16:45 Coffee break 16:45-18:00 Afternoon session III 16:45-16:55 TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt and Nazli Goharian 16:55-17:00 A New Dataset and Efficient Baselines for Document-level Text Simplification in German Annette Rios, Nicolas Spring, Tannon Kew, Marek Kostrzewa, Andreas S\u00e4uberli, Mathias M\u00fcller and Sarah Ebling 17:00-18:00 Mentoring Program", | |
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| "content": "<table><tr><td>Alexander Fabbri (Yale University)</td></tr><tr><td>Greg Durrett (UT Austin)</td></tr><tr><td>Yang Gao (Royal Holloway, University of London, UK)</td></tr><tr><td>Ramakanth Pasunuru (UNC Chapel Hill)</td></tr><tr><td>Ido Dagan (Bar-Ilan University)</td></tr><tr><td>Enamul Hoque (York University)</td></tr><tr><td>Jiacheng Xu (The University of Texas at Austin)</td></tr><tr><td>Rui Zhang (Penn State University)</td></tr><tr><td>Hou Pong Chan (University of Macau)</td></tr><tr><td>Yuntian Deng (Harvard University)</td></tr><tr><td>Kristjan Arumae (Amazon)</td></tr><tr><td>Xiaojun Wan (Peking University)</td></tr><tr><td>Chris Kedzie (Rasa Technologies Inc.)</td></tr><tr><td>Naoaki Okazaki (Tokyo Institute of Technology)</td></tr><tr><td>Manabu Okumura (Tokyo Institute of Technology)</td></tr><tr><td>Yang Liu (Microsoft)</td></tr><tr><td>Tadashi Nomoto (National Institute of Japanese Literature)</td></tr><tr><td>Linzi Xing (University of British Columbia)</td></tr><tr><td>Ari Rappoport (Hebrew University)</td></tr><tr><td>Felice Dell'Orletta (Istituto di Linguistica Computazionale \"A. Zampolli\" (CNR), Pisa, Italy)</td></tr><tr><td>Margot Mieskes (University of Applied Sciences Darmstadt, Germany)</td></tr><tr><td>Rodrigo Souza Wilkens (University of Essex)</td></tr><tr><td>Maxime Peyrard (EPFL)</td></tr><tr><td>Benoit Favre (Aix-Marseille University LIS/CNRS)</td></tr><tr><td>Tobias Falke (Amazon)</td></tr><tr><td>Thiago Alexandre Salgueiro Pardo (University of S\u00e3o Paulo)</td></tr><tr><td>Jessica Ouyang (University of Texas at Dallas)</td></tr><tr><td>Wencan Luo (Google)</td></tr><tr><td>Florian Boudin (Universit\u00e9 de Nantes -France)</td></tr><tr><td>Juan-Manuel Torres-Moreno (LIA Avignon Universit\u00e9)</td></tr><tr><td>Michael Elhadad (Ben Gurion University)</td></tr><tr><td>Esa\u00fa Villatoro Tello (Universidad Aut\u00f3noma Metropolitana Unidad Cuajimalpa, M\u00e9xico)</td></tr><tr><td>Yuning Mao (University of Illinois at Urbana-Champaign)</td></tr><tr><td>Wen Xiao (University of British Columbia)</td></tr><tr><td>Xinyu Hua (Northeastern University)</td></tr><tr><td>Patrick Huber (University of British Columbia)</td></tr><tr><td>Abram Handler (University of Colorado)</td></tr><tr><td>Wojciech Kry\u015bci\u0144ski (Salesforce Research)</td></tr><tr><td>v</td></tr></table>", | |
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| "text": "Sentence-level Planning for Especially Abstractive Summarization Andreas Marfurt and James Henderson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Template-aware Attention Model for Earnings Call Report Generation Yangchen Huang, Prashant K. Dhingra and Seyed Danial Mohseni Taheri . . . . . . . . . . . . . . . . . . . . 15", | |
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