| { |
| "paper_id": "P16-1000", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T08:55:50.914709Z" |
| }, |
| "title": "Preface: General Chair", |
| "authors": [ |
| { |
| "first": "Pushpak", |
| "middle": [], |
| "last": "Manning", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Joakim", |
| "middle": [], |
| "last": "Bhattacharyya", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Graeme", |
| "middle": [], |
| "last": "Nivre", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dragomir", |
| "middle": [], |
| "last": "Hirst", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gertjan", |
| "middle": [], |
| "last": "Radev", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Min-Yen", |
| "middle": [], |
| "last": "Van Nood", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Herman", |
| "middle": [], |
| "last": "Kan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yejin", |
| "middle": [], |
| "last": "Ney", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Choi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mark", |
| "middle": [], |
| "last": "Steedman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Miguel", |
| "middle": [], |
| "last": "Ballesteros", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Bam- Man", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Steven", |
| "middle": [], |
| "last": "Bethard", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jonathan", |
| "middle": [], |
| "last": "Berant", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gemma", |
| "middle": [], |
| "last": "Boleda", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ming-Wei", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Wanxiang", |
| "middle": [], |
| "last": "Che", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Chris", |
| "middle": [], |
| "last": "Dyer", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ed", |
| "middle": [], |
| "last": "Grefenstette", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hannaneh", |
| "middle": [], |
| "last": "Hajishirzi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Minlie", |
| "middle": [], |
| "last": "Huang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mans", |
| "middle": [], |
| "last": "Hulden", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Heng", |
| "middle": [], |
| "last": "Ji", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jing", |
| "middle": [], |
| "last": "Jiang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Zornitsa", |
| "middle": [], |
| "last": "Kozareva", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marco", |
| "middle": [], |
| "last": "Kuhlmann", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yang", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Annie", |
| "middle": [], |
| "last": "Louis", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Wei", |
| "middle": [], |
| "last": "Lu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marie-Catherine", |
| "middle": [], |
| "last": "De Marneffe", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gerard", |
| "middle": [], |
| "last": "De Melo", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Mimno", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Meg", |
| "middle": [], |
| "last": "Mitchell", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daichi", |
| "middle": [], |
| "last": "Mochihashi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Graham", |
| "middle": [], |
| "last": "Neubig", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Naoaki", |
| "middle": [], |
| "last": "Okazaki", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Simone", |
| "middle": [], |
| "last": "Ponzetto", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Matthew", |
| "middle": [], |
| "last": "Purver", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Reitter", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nathan", |
| "middle": [], |
| "last": "Schneider", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hinrich", |
| "middle": [], |
| "last": "Schuetze", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Thamar", |
| "middle": [], |
| "last": "Solorio", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Lucia", |
| "middle": [], |
| "last": "Specia", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Partha", |
| "middle": [], |
| "last": "Talukdar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ivan", |
| "middle": [], |
| "last": "Titov", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Lu", |
| "middle": [], |
| "last": "Wang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nianwen", |
| "middle": [], |
| "last": "Xue", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jinyeong", |
| "middle": [], |
| "last": "Bak", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Collin", |
| "middle": [], |
| "last": "Baker", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Alexandra", |
| "middle": [], |
| "last": "Balahur", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Timothy", |
| "middle": [], |
| "last": "Baldwin", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Borja", |
| "middle": [], |
| "last": "Balle", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Bamman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Srinivas", |
| "middle": [], |
| "last": "Bangalore", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mohit", |
| "middle": [], |
| "last": "Bansal", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Libby", |
| "middle": [], |
| "last": "Barak", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marco", |
| "middle": [], |
| "last": "Baroni", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Regina", |
| "middle": [], |
| "last": "Barzilay", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Roberto", |
| "middle": [], |
| "last": "Basili", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Batista", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Timo", |
| "middle": [], |
| "last": "Baumann", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Frederic", |
| "middle": [], |
| "last": "Bechet", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daniel", |
| "middle": [], |
| "last": "Beck", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "N\u00faria", |
| "middle": [], |
| "last": "Bel", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "I", |
| "middle": [], |
| "last": "Beltagy", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Anja", |
| "middle": [], |
| "last": "Belz", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Fabr\u00edcio", |
| "middle": [], |
| "last": "Benevenuto", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Taylor", |
| "middle": [], |
| "last": "Berg-Kirkpatrick", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sabine", |
| "middle": [], |
| "last": "Bergler", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Raffaella", |
| "middle": [], |
| "last": "Bernardi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Robert", |
| "middle": [], |
| "last": "Berwick", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Archna", |
| "middle": [], |
| "last": "Bhatia", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Pushpak", |
| "middle": [], |
| "last": "Bhattacharyya", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Klinton", |
| "middle": [], |
| "last": "Bicknell", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ann", |
| "middle": [], |
| "last": "Bies", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Alexandra", |
| "middle": [], |
| "last": "Birch", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Anders", |
| "middle": [], |
| "last": "Bj\u00f6rkelund", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Fr\u00e9d\u00e9ric", |
| "middle": [], |
| "last": "Blain", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nate", |
| "middle": [], |
| "last": "Blaylock", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Bernd", |
| "middle": [], |
| "last": "Bohnet", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ond\u0159ej", |
| "middle": [], |
| "last": "Bojar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ester", |
| "middle": [], |
| "last": "Boldrini", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Danushka", |
| "middle": [], |
| "last": "Bollegala", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Claire", |
| "middle": [], |
| "last": "Bonial", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Georgeta", |
| "middle": [], |
| "last": "Bordea", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Antoine", |
| "middle": [], |
| "last": "Bordes", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Johan", |
| "middle": [], |
| "last": "Bos", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Samuel", |
| "middle": [ |
| "R" |
| ], |
| "last": "Bow- Man", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Johan", |
| "middle": [], |
| "last": "Boye", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kristy", |
| "middle": [], |
| "last": "Boyer", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Cem", |
| "middle": [], |
| "last": "Bozsahin", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "S", |
| "middle": [ |
| "R K" |
| ], |
| "last": "Branavan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ant\u00f3nio", |
| "middle": [], |
| "last": "Branco", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Adrian", |
| "middle": [], |
| "last": "Brasoveanu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Elia", |
| "middle": [], |
| "last": "Bruni", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Christian", |
| "middle": [], |
| "last": "Buck", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Paul", |
| "middle": [], |
| "last": "Buitelaar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Harry", |
| "middle": [], |
| "last": "Bunt", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hendrik", |
| "middle": [], |
| "last": "Buschmeier", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Aoife", |
| "middle": [], |
| "last": "Cahill", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Lynne", |
| "middle": [], |
| "last": "Cahill", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jos\u00e9", |
| "middle": [], |
| "last": "Camacho-Collados", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Burcu", |
| "middle": [], |
| "last": "Can", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nicola", |
| "middle": [], |
| "last": "Cancedda", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hailong", |
| "middle": [], |
| "last": "Cao", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kris", |
| "middle": [], |
| "last": "Cao", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yunbo", |
| "middle": [], |
| "last": "Cao", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Claire", |
| "middle": [], |
| "last": "Cardie", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Xavier", |
| "middle": [], |
| "last": "Carreras", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "John", |
| "middle": [], |
| "last": "Carroll", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Paula", |
| "middle": [], |
| "last": "Carvalho", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Francisco", |
| "middle": [], |
| "last": "Casacuberta", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Helena", |
| "middle": [], |
| "last": "Caseli", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tommaso", |
| "middle": [], |
| "last": "Caselli", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Steve", |
| "middle": [], |
| "last": "Cassidy", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Irene", |
| "middle": [], |
| "last": "Castellon", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Giuseppe", |
| "middle": [], |
| "last": "Castellucci", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Asli", |
| "middle": [], |
| "last": "Celikyilmaz", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "\u00d6zlem", |
| "middle": [ |
| "\u00c7" |
| ], |
| "last": "Etinoglu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mauro", |
| "middle": [], |
| "last": "Cettolo", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Arun", |
| "middle": [], |
| "last": "Chaganty", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hou-Pong", |
| "middle": [], |
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| "first": "Kai-Wei", |
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| { |
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| { |
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| { |
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| { |
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| { |
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| { |
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| { |
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| { |
| "first": "David", |
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| "email": "" |
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| { |
| "first": "Hai", |
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| "last": "Leong Chieu", |
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| "email": "" |
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| { |
| "first": "Yejin", |
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| "last": "Choi", |
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| "email": "" |
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| { |
| "first": "Janara", |
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| "email": "" |
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| { |
| "first": "Christos", |
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| "last": "Christodoulopoulos", |
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| "email": "" |
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| { |
| "first": "Grzegorz", |
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| "last": "Chrupa\u0142a", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Alexander", |
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| "last": "Clark", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Stephen", |
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| "affiliation": {}, |
| "email": "" |
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| { |
| "first": "Ann", |
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| "last": "Clifton", |
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| "affiliation": {}, |
| "email": "" |
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| { |
| "first": "Maximin", |
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| "last": "Coavoux", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Moreno", |
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| "last": "Coco", |
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| "email": "" |
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| { |
| "first": "Trevor", |
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| "last": "Cohn", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sandra", |
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| "last": "Collovini", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Miriam", |
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| "last": "Connor", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "John", |
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| "last": "Conroy", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Paul", |
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| "last": "Cook", |
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| "affiliation": {}, |
| "email": "" |
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| { |
| "first": "Ann", |
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| "last": "Copestake", |
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| "affiliation": {}, |
| "email": "" |
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| { |
| "first": "Ryan", |
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| "last": "Cotterell", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Benoit", |
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| "last": "Crabb\u00e9", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Danilo", |
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| "last": "Croce", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "James", |
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| "last": "Cross", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Montse", |
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| "last": "Cuadros", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Heriberto", |
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| "last": "Cuayahuitl", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Silviu-Petru", |
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| "last": "Cucerzan", |
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| "affiliation": {}, |
| "email": "" |
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| { |
| "first": "Xiaodong", |
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| "last": "Cui", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jennifer", |
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| "last": "Culbertson", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Aron", |
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| "last": "Culotta", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Walter", |
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| "last": "Daelemans", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Robert", |
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| "last": "Daland", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Amitava", |
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| "last": "Das", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dipanjan", |
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| "last": "Das", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hal", |
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| "last": "Daum\u00e9", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Brian", |
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| "last": "Davison", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "De", |
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| "last": "Choudhury", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Adri\u00e0", |
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| "last": "De Gispert", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Claudio", |
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| "last": "Delli Bovi", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Vera", |
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| "last": "Demberg", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Pascal", |
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| "last": "Denis", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
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| "last": "Denkowski", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Leon", |
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| "last": "Derczynski", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Aliya", |
| "middle": [], |
| "last": "Deri", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nina", |
| "middle": [], |
| "last": "Dethlefs", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ann", |
| "middle": [], |
| "last": "Devitt", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ja- Cob", |
| "middle": [], |
| "last": "Devlin", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Giuseppe", |
| "middle": [ |
| "Di" |
| ], |
| "last": "Fabbrizio", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mona", |
| "middle": [], |
| "last": "Diab", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Brian", |
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| "last": "Dillon", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Georgiana", |
| "middle": [], |
| "last": "Dinu", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dmitriy", |
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| "last": "Dligach", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Simon", |
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| "last": "Dobnik", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ellen", |
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| "last": "Dodge", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "A", |
| "middle": [ |
| "Seza" |
| ], |
| "last": "Dogru\u00f6z", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Doug", |
| "middle": [], |
| "last": "Downey", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Eduard", |
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| "last": "Dragut", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mark", |
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| "last": "Dras", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Markus", |
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| "last": "Dreyer", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gre- Gory", |
| "middle": [], |
| "last": "Druck", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Lan", |
| "middle": [], |
| "last": "Du", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kevin", |
| "middle": [], |
| "last": "Duh", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jesse", |
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| "last": "Dunietz", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Long", |
| "middle": [], |
| "last": "Duong", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nadir", |
| "middle": [], |
| "last": "Durrani", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Greg", |
| "middle": [], |
| "last": "Durrett", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marc", |
| "middle": [], |
| "last": "Dymetman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Koji", |
| "middle": [], |
| "last": "Eguchi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Patrick", |
| "middle": [], |
| "last": "Ehlen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Vladimir", |
| "middle": [], |
| "last": "Eidelman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Andreas", |
| "middle": [], |
| "last": "Eisele", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jacob", |
| "middle": [], |
| "last": "Eisenstein", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jason", |
| "middle": [], |
| "last": "Eisner", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
| "middle": [], |
| "last": "Elhadad", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Micha", |
| "middle": [], |
| "last": "Elsner", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nikolaos", |
| "middle": [], |
| "last": "Engonopoulos", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Katrin", |
| "middle": [], |
| "last": "Erk", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Miquel", |
| "middle": [], |
| "last": "Espl\u00e0-Gomis", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Paula", |
| "middle": [], |
| "last": "Estrella", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Keelan", |
| "middle": [], |
| "last": "Evanini", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Federico", |
| "middle": [], |
| "last": "Fancellu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Rui", |
| "middle": [], |
| "last": "Fang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Manaal", |
| "middle": [], |
| "last": "Faruqui", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Adam", |
| "middle": [], |
| "last": "Faulkner", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Benoit", |
| "middle": [], |
| "last": "Favre", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Anna", |
| "middle": [], |
| "last": "Feldman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Naomi", |
| "middle": [], |
| "last": "Feld- Man", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Raquel", |
| "middle": [], |
| "last": "Fernandez", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daniel", |
| "middle": [], |
| "last": "Fern\u00e1ndez-Gonz\u00e1lez", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Simone", |
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| "last": "Filice", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Katja", |
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| "last": "Filippova", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Orhan", |
| "middle": [], |
| "last": "Firat", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nicholas", |
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| "last": "Fitzgerald", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Margaret", |
| "middle": [], |
| "last": "Fleck", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Fabian", |
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| "last": "Fl\u00f6ck", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Enrique", |
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| "last": "Flores", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Evandro", |
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| "last": "Fonseca", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mikel", |
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| "last": "Forcada", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dayne", |
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| "last": "Fraser", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Annemarie", |
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| "last": "Freitag", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Akinori", |
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| "last": "Friedrich", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yarin", |
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| "last": "Fujino", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michel", |
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| "last": "Gal", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Carlos", |
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| "last": "Galley", |
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| "email": "" |
| }, |
| { |
| "first": "Bj\u00f6rn", |
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| "last": "Gallo", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
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| "last": "Gamb\u00e4ck", |
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| "email": "" |
| }, |
| { |
| "first": "Kuzman", |
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| "last": "Gamon", |
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| "email": "" |
| }, |
| { |
| "first": "Kavita", |
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| "last": "Ganchev", |
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| "email": "" |
| }, |
| { |
| "first": "Juri", |
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| "last": "Gane- San", |
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| "email": "" |
| }, |
| { |
| "first": "Jianfeng", |
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| "last": "Ganitkevitch", |
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| "email": "" |
| }, |
| { |
| "first": "Wei", |
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| "last": "Gao", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Miguel", |
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| "A" |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Claire", |
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| "last": "Garc\u00eda-Cumbreras", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Matt", |
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| "last": "Gardent", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dan", |
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| "last": "Gard- Ner", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Milica", |
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| "last": "Garrette", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kallirroi", |
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| "last": "Gasic", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daniel", |
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| "last": "Georgila", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kevin", |
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| "last": "Gildea", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Maite", |
| "middle": [], |
| "last": "Gimpel", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jonathan", |
| "middle": [], |
| "last": "Gim\u00e9nez", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dimitra", |
| "middle": [], |
| "last": "Ginzburg", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Goran", |
| "middle": [], |
| "last": "Gkatzia", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Amir", |
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| "last": "Glava\u0161", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yoav", |
| "middle": [], |
| "last": "Globerson", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dan", |
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| "last": "Goldberg", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sharon", |
| "middle": [], |
| "last": "Goldwasser", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Carlos", |
| "middle": [], |
| "last": "G\u00f3mez-Rodr\u00edguez", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Edgar", |
| "middle": [], |
| "last": "Gonz\u00e1lez", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Matthew", |
| "middle": [ |
| "R" |
| ], |
| "last": "Gormley", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Cyril", |
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| "last": "Goutte", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Joao", |
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| "last": "Graca", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tom", |
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| "last": "Griffis", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Liane", |
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| "last": "Griffiths", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Curry", |
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| "last": "Guillou", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "James", |
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| "last": "Guinn", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jiang", |
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| "last": "Gung", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Weiwei", |
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| "last": "Guo", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yuhong", |
| "middle": [], |
| "last": "Guo", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Abhijeet", |
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| "last": "Guo", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Iryna", |
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| "last": "Gupta", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yoan", |
| "middle": [], |
| "last": "Gurevych", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kelvin", |
| "middle": [], |
| "last": "Gutierrez", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nizar", |
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| "last": "Guu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gholamreza", |
| "middle": [], |
| "last": "Habash", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hannaneh", |
| "middle": [], |
| "last": "Haffari", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dilek", |
| "middle": [], |
| "last": "Hajishirzi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "John", |
| "middle": [], |
| "last": "Hakkani-Tur", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Hale", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Keith", |
| "middle": [], |
| "last": "Hall", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "William", |
| "middle": [ |
| "L" |
| ], |
| "last": "Hall", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
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| "last": "Hamilton", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Bo", |
| "middle": [], |
| "last": "Hammond", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Greg", |
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| "last": "Han", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Christian", |
| "middle": [], |
| "last": "Hanneman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sasa", |
| "middle": [], |
| "last": "Hardmeier", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Helen", |
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| "last": "Hasan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Claudia", |
| "middle": [], |
| "last": "Hastie", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Katsuhiko", |
| "middle": [], |
| "last": "Hauff", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daqing", |
| "middle": [], |
| "last": "Hayashi", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Luheng", |
| "middle": [], |
| "last": "He", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Xiaodong", |
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| "last": "He", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yifan", |
| "middle": [], |
| "last": "He", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ken- Neth", |
| "middle": [], |
| "last": "He", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Carmen", |
| "middle": [], |
| "last": "Heafield", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
| "middle": [], |
| "last": "Heger", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "James", |
| "middle": [], |
| "last": "Heilman", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Matthew", |
| "middle": [], |
| "last": "Henderson", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Aur\u00e9lie", |
| "middle": [], |
| "last": "Henderson", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Karl", |
| "middle": [], |
| "last": "Herbelot", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hermann", |
| "middle": [], |
| "last": "Moritz", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Daniel", |
| "middle": [], |
| "last": "Hershcovich", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jack", |
| "middle": [], |
| "last": "Hessel", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Felix", |
| "middle": [], |
| "last": "Hill", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Keikichi", |
| "middle": [], |
| "last": "Hirose", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Graeme", |
| "middle": [], |
| "last": "Hirst", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Julian", |
| "middle": [], |
| "last": "Hitschler", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Anna", |
| "middle": [], |
| "last": "Hjalmarsson", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kai", |
| "middle": [], |
| "last": "Hong", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Andrea", |
| "middle": [], |
| "last": "Hong", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Julian", |
| "middle": [], |
| "last": "Horbach", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dirk", |
| "middle": [], |
| "last": "Hough", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Bo- June", |
| "middle": [], |
| "last": "Hovy", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Paul", |
| "middle": [], |
| "last": "Hsu", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Liang", |
| "middle": [], |
| "last": "Huang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ruihong", |
| "middle": [], |
| "last": "Huang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tim", |
| "middle": [], |
| "last": "Hunter", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jena", |
| "middle": [ |
| "D" |
| ], |
| "last": "Hwang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Cassandra", |
| "middle": [ |
| "L" |
| ], |
| "last": "Jacobs", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Guillaume", |
| "middle": [], |
| "last": "Jacquet", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Evan", |
| "middle": [], |
| "last": "Jaffe", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jagadeesh", |
| "middle": [], |
| "last": "Jagarlamudi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Zunaira", |
| "middle": [], |
| "last": "Jamil", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Peter", |
| "middle": [], |
| "last": "Jansen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Laura", |
| "middle": [], |
| "last": "Jehl", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yacine", |
| "middle": [], |
| "last": "Jernite", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yangfeng", |
| "middle": [], |
| "last": "Ji", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sittichai", |
| "middle": [], |
| "last": "Jiampojamarn", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Wenbin", |
| "middle": [], |
| "last": "Jiang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Xin", |
| "middle": [], |
| "last": "Jiang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Salud", |
| "middle": [], |
| "last": "Mar\u00eda", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jim\u00e9nez", |
| "middle": [], |
| "last": "Zafra", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Anders", |
| "middle": [], |
| "last": "Johannsen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Richard", |
| "middle": [], |
| "last": "Johansson", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Michael", |
| "middle": [], |
| "last": "Johnston", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kristiina", |
| "middle": [], |
| "last": "Joki- Nen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Arne", |
| "middle": [], |
| "last": "Jonsson", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Aditya", |
| "middle": [], |
| "last": "Joshi", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Shafiq", |
| "middle": [], |
| "last": "Joty", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Dan", |
| "middle": [], |
| "last": "Jurafsky", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Filip", |
| "middle": [], |
| "last": "Jurcicek", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Jurgens", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mijail", |
| "middle": [], |
| "last": "Kabadjov", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nobuhiro", |
| "middle": [], |
| "last": "Kaji", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jaap", |
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| "last": "Kamps", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Min-Yen", |
| "middle": [], |
| "last": "Kan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Hiroshi", |
| "middle": [], |
| "last": "Kanayama", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Mladen", |
| "middle": [], |
| "last": "Karan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tatsuya", |
| "middle": [], |
| "last": "Kawahara", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Frank", |
| "middle": [], |
| "last": "Keller", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Casey", |
| "middle": [], |
| "last": "Kennington", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Chlo\u00e9", |
| "middle": [], |
| "last": "Kiddon", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Douwe", |
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| "last": "Kiela", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jae", |
| "middle": [ |
| "Won" |
| ], |
| "last": "Kim", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Joon", |
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| "last": "Kim", |
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| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jooyeon", |
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| "abstract": "In my welcome to participants in this year's conference handbook, I especially welcomed those for which it was their first ACL. I expressed the hope that the conference fulfilled their expectations and remained in their memory as a great start. Trying to imagine the first experience of a present-day ACL, the magnitude of the whole event may be a bit overwhelming-our field is on an expanding trajectory, and even a selection of the best work fills a great number of parallel sessions over a number of days; plus, there are the workshops and tutorials to quench many topical thirsts. This ACL again promises to be a next peak in a progressive development. ACL Conferences are the product of many people working together, kindly offering their services to the community at large. ACL-2016 is no exception to this. I would like to thank each and every person who has volunteered their time to make the event possible. I am deeply impressed with the sense of community that organizing an ACL brings about.", |
| "pdf_parse": { |
| "paper_id": "P16-1000", |
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| "abstract": [ |
| { |
| "text": "In my welcome to participants in this year's conference handbook, I especially welcomed those for which it was their first ACL. I expressed the hope that the conference fulfilled their expectations and remained in their memory as a great start. Trying to imagine the first experience of a present-day ACL, the magnitude of the whole event may be a bit overwhelming-our field is on an expanding trajectory, and even a selection of the best work fills a great number of parallel sessions over a number of days; plus, there are the workshops and tutorials to quench many topical thirsts. This ACL again promises to be a next peak in a progressive development. ACL Conferences are the product of many people working together, kindly offering their services to the community at large. ACL-2016 is no exception to this. I would like to thank each and every person who has volunteered their time to make the event possible. I am deeply impressed with the sense of community that organizing an ACL brings about.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Abstract", |
| "sec_num": null |
| } |
| ], |
| "body_text": [ |
| { |
| "text": "The Importance of Tone and Framing in Language Amber E. Boydstun, University of California at Davis Many policy issues at the center of politics are relatively fixed; they tend to involve the same basic questions that do not vary over time (e.g., should abortion be legal? should we execute people convicted of horrific crimes?). Political candidates, too, are (like the rest of us) the same people year after year (e.g., Hillary Clinton in 2016 is just an older version of Hillary Clinton in 2015). Yet when citizens consider a given political item (be it a policy issue, a candidate, or something else), they tend not to perceive that item in a fixed way over time. Rather, peoples perceptions of the item tend to depend on how that item is portrayed at that moment. Policy issues and political candidates alike can be portrayed differently through the use of different visual imagery but even more pervasively through variance in the text used to describe them. In this talk, I give a general overview of the importance of issue and candidate portrayals in political communication. I outline the extensive research that has already been done trying to identify different portrayals in text. And I discuss the many opportunities available today to researchers interested in tracking issue and candidate portrayals in text and in examining the effects of issue and candidate portrayals on public attitudes and voting behavior.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Invited Talk I: Same Policy Issue, Different Portrayal:", |
| "sec_num": null |
| }, |
| { |
| "text": "Bio: Amber Boydstun is an Associate Professor of Political Science at the University of California, Davis. Her work bridges multiple disciplines, including psychology, journalism, and computer science. Her core research examines the interaction between media and politics, with a focus on how different media portrayals of the same policy issue can prompt citizens and policymakers to respond to that issue in different ways. She uses lab experiments, large-scale media studies, and manual and computational text analysis to study how issues make the news; how issues are \"framed\" in the news; the dynamics of \"media storms\"; and how media coverage can shape public opinion and public policy on issues like immigration, gun control, samesex marriage, and capital punishment. She is author of Making the News (Chicago) and co-author of The Decline of the Death Penalty and the Discovery of Innocence (Cambridge), as well as many journal articles. Boydstun works with scholars across the globe as a member of the Comparative Agendas Project, 1 a collaborative enterprise by political science and policy scholars to measure international government outputs. She serves on the editorial boards for the journal Political Communication, the Text as Data Association, and the Women Also Know Stuff 2 initiative. Most recently, she co-chaired the 2016 Visions in Methodology Conference. 3", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Invited Talk I: Same Policy Issue, Different Portrayal:", |
| "sec_num": null |
| }, |
| { |
| "text": "The central problem in open domain-question answering from text is the problem of entailment. Given enough text, the answer is almost certain to be there, but is likely to be expressed differently than in the question-either in a paraphrase, or in a sentence that entails or implies the answer. We cannot afford to bridge this gap by open-ended theorem-proving search. Instead we need a semantics for natural language that directly supports common-sense inference, such as that arriving somewhere implies subsequently being there, and invading a country implies attacking it. We would like this semantics to be compatible with traditional logical operator semantics including quantification, negation and tense, so that not being there implies not having arrived, and not attacking implies not invading.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "There have been many attempts to build such a semantics of content words by hand, from the generative semantics of the '60s to WordNet and other resources of the present. The '60s saw attempts based on generative semantics, while more recently, they have exploited WordNet and other computational resources. However, such systems have been incomplete and language-specific in comparison to the vastness of human common-sense reasoning. One consequence has been renewed interest in the idea of treating the semantics as \"hidden\", to be discovered through machine learning, an idea that has its origins in the \"semantic differential\" of Osgood, Suci, and Tannenbaum in the '50s.", |
| "cite_spans": [], |
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| "eq_spans": [], |
| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "There are two distinct modern approaches to the problem of data-driven or \"distributional\" semantics. The first, which I will call \"collocational\", is the direct descendant of the semantic differential. In its most basic form, the meaning of a word is taken to be a vector in a space whose dimensions are defined by the lexicon of the language, and whose magnitude is defined by counts of those lexical items within a fixed window on the string (although in practice the dimensionality is reduced and the relation to frequency less direct). Crucially, semantic composition is defined in terms of linear algebraic operations such as vector addition.", |
| "cite_spans": [], |
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| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "The second approach, which I will call \"denotational\", defines the meaning of a word in terms of the entities (or rather their designators) that it is predicated over and the ensembles of predications over entities of the same types, obtained by machine-reading with wide coverage parsers. Semantic composition is can then be defined as an applicative system, as in traditional formal semantics.", |
| "cite_spans": [], |
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| "eq_spans": [], |
| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "The talk reviews recent work in both collocation-and denotation-based distributional semantics, including some hybrid approaches that interpolate grammatical features with collocational representations, or use probabilistic logics over relations whose arguments denote vectors, and asks for each what dimensions of meaning are actually being represented. It argues that the two approaches are largely orthogonal on these dimensions. Collocational representations are good for representing ambiguity, with linear algebraic composition most effective at disambiguation and representing distributional similarity. Denotational representations represent something more like a traditional compositional semantics, but one in which the primitive relations correspond to those of a hidden language of logical form representing paraphrase and common-sense entailment directly.", |
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| "eq_spans": [], |
| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "To make this point, I will discuss recent work in which collocational distributional representations such as embeddings have been used as proxies for semantic features in models such as LSTM, to guide disambiguation during parsing, while a lexicalized denotation-based distributional semantics is used to support inference of entailment. I will show that this hybrid approach can be applied with a number of parsing mod-els, including transition-based and supertagging, to support entailment-based QA with denotation-based distributional representations. I will discuss work at Edinburgh and elsewhere in which the semantics of paraphrases is represented by a single cluster identifier and common-sense inference (derived from a learned entailment graph) is built into the lexicon and projected by syntactic derivation, rather than delegated to a later stage of inference. The method can be applied cross-linguistically, in support of machine translation. Ongoing work extends the method to extract multi-word items, light-verb constructions, and an aspect-based semantics for temporal/causal entailment, and to the creation and interrogation of Knowledge Graphs and Semantic Nets via natural language. His research interests cover issues in computational linguistics, artificial intelligence, computer science and cognitive science, including syntax and semantics of natural language, wide-coverage parsing and questionanswering, comprehension of natural language discourse by humans and by machine, grammar-based language modeling, natural language generation, and the semantics of intonation in spoken discourse. Much of his current NLP research is addressed to probabilistic parsing and robust semantics for question-answering using the CCG grammar formalism, including the acquisition of language from paired sentences and meanings by child and machine. He sometimes works with colleagues in computer animation using these theories to guide the graphical animation of speaking virtual or simulated autonomous human agents. Some of his research concerns the analysis of music by humans and machines. ", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Invited Talk II: On Distributional Semantics Mark Steedman, University of Edinburgh", |
| "sec_num": null |
| }, |
| { |
| "text": "http://www.comparativeagendas.info/ 2 http://womenalsoknowstuff.com/ 3 http://visionsinmethodology.org/conferences/2016-conference/xv", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "", |
| "sec_num": null |
| } |
| ], |
| "back_matter": [], |
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| "raw_text": "Monday, August 8, (continued) Session 1B: Information extraction 10:40-11:00 Unsupervised Person Slot Filling based on Graph Mining Dian Yu and Heng Ji 11:20-11:40 A Multi-media Approach to Cross-lingual Entity Knowledge Transfer Di Lu, Xiaoman Pan, Nima Pourdamghani, Shih-Fu Chang, Heng Ji and Kevin Knight Session 1C: Machine translation I 10:40-11:00 Models and Inference for Prefix-Constrained Machine Translation Joern Wuebker, Spence Green, John DeNero, Sasa Hasan and Minh-Thang Luong 11:00-11:20 Modeling Coverage for Neural Machine Translation Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu and Hang Li 11:20-11:40 Improving Neural Machine Translation Models with Monolingual Data Rico Sennrich, Barry Haddow and Alexandra Birch 11:40-12:00 Graph-Based Translation Via Graph Segmentation Liangyou Li, Andy Way and Qun Liu Session 1D: Word meaning I 10:40-11:00 Incremental Acquisition of Verb Hypothesis Space towards Physical World Interac- tion Lanbo She and Joyce Chai 11:00-11:20 Language Transfer Learning for Supervised Lexical Substitution Gerold Hintz and Chris Biemann 11:20-11:40 Learning the Curriculum with Bayesian Optimization for Task-Specific Word Rep- resentation Learning Yulia Tsvetkov, Manaal Faruqui, Wang Ling, Brian MacWhinney and Chris Dyer 11:40-12:00 Pointing the Unknown Words Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou and Yoshua Bengio xxxiv", |
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| "raw_text": "Monday, August 8, 2016 (continued) Session 1E: Parsing I 11:00-11:20 Generalized Transition-based Dependency Parsing via Control Parameters Bernd Bohnet, Ryan McDonald, Emily Pitler and Ji Ma 11:20-11:40 A Transition-Based System for Joint Lexical and Syntactic Analysis Matthieu Constant and Joakim Nivre 11:40-12:00 Neural Greedy Constituent Parsing with Dynamic Oracles Maximin Coavoux and Benoit Crabb\u00e9 Session 1F: Noncompositionality 10:40-11:00 Literal and Metaphorical Senses in Compositional Distributional Semantic Models E.Dario Gutierrez, Ekaterina Shutova, Tyler Marghetis and Benjamin Bergen 11:00-11:20 Idiom Token Classification using Sentential Distributed Semantics Giancarlo Salton, Robert Ross and John Kelleher 11:20-11:40 Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embed- dings Kazuma Hashimoto and Yoshimasa Tsuruoka 11:40-12:00 Metaphor Detection with Topic Transition, Emotion and Cognition in Context Hyeju Jang, Yohan Jo, Qinlan Shen, Michael Miller, Seungwhan Moon and Carolyn Rose 12:00-13:40 Lunch break xxxv", |
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| "num": null, |
| "urls": [], |
| "raw_text": "Monday, August 8, 2016 (continued) Session 2C: Sentiment analysis 13:40-14:00 Sentiment Domain Adaptation with Multiple Sources Fangzhao Wu and Yongfeng Huang 14:00-14:20 Connotation Frames: A Data-Driven Investigation Hannah Rashkin, Sameer Singh and Yejin Choi 14:20-14:40 Bi-Transferring Deep Neural Networks for Domain Adaptation Guangyou Zhou, Zhiwen Xie, Jimmy Xiangji Huang and Tingting He 14:40-15:00 Document-level Sentiment Inference with Social, Faction, and Discourse Context Eunsol Choi, Hannah Rashkin, Luke Zettlemoyer and Yejin Choi Session 2D: Parsing II 13:40-14:00 Active Learning for Dependency Parsing with Partial Annotation Zhenghua Li, Min Zhang, Yue Zhang, Zhanyi Liu, Wenliang Chen, Hua Wu and Haifeng Wang 14:20-14:40 Dependency Parsing with Bounded Block Degree and Well-nestedness via La- grangian Relaxation and Branch-and-Bound Caio Corro, Joseph Le Roux, Mathieu Lacroix, Antoine Rozenknop and Roberto Wolfler Calvo Session 2E: Information retrieval 13:40-14:00 Query Expansion with Locally-Trained Word Embeddings Fernando Diaz, Bhaskar Mitra and Nick Craswell 14:00-14:20 Together we stand: Siamese Networks for Similar Question Retrieval Arpita Das, Harish Yenala, Manoj Chinnakotla and Manish Shrivastava 14:20-14:40 News Citation Recommendation with Implicit and Explicit Semantics Hao Peng, Jing Liu and Chin-Yew Lin xxxvii", |
| "links": null |
| }, |
| "BIBREF40": { |
| "ref_id": "b40", |
| "title": ":00 Transition-Based Neural Word Segmentation Meishan Zhang, Yue Zhang and Guohong Fu 15:00-15:30 Coffee break Session 3A: Question answering I 15:30-15:50 A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data Adam Trischler", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Monday", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "30 Easy Questions First? A Case Study on Curriculum Learning for Question Answering Mrinmaya Sachan and Eric Xing", |
| "volume": "14", |
| "issue": "", |
| "pages": "50--67", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Monday, August 8, (continued) Session 2F: Phonology and morphology 13:40-14:00 Grapheme-to-Phoneme Models for (Almost) Any Language Aliya Deri and Kevin Knight 14:20-14:40 Neural Word Segmentation Learning for Chinese Deng Cai and Hai Zhao 14:40-15:00 Transition-Based Neural Word Segmentation Meishan Zhang, Yue Zhang and Guohong Fu 15:00-15:30 Coffee break Session 3A: Question answering I 15:30-15:50 A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data Adam Trischler, Zheng Ye, Xingdi Yuan, Jing He and Philip Bachman 15:50-16:10 Combining Natural Logic and Shallow Reasoning for Question Answering Gabor Angeli, Neha Nayak and Christopher D. Manning 16:10-16:30 Easy Questions First? A Case Study on Curriculum Learning for Question Answer- ing Mrinmaya Sachan and Eric Xing 16:30-16:50 Improved Representation Learning for Question Answer Matching Ming Tan, Cicero dos Santos, Bing Xiang and Bowen Zhou 16:50-17:10 Tables as Semi-structured Knowledge for Question Answering Sujay Kumar Jauhar, Peter Turney and Eduard Hovy xxxviii", |
| "links": null |
| }, |
| "BIBREF41": { |
| "ref_id": "b41", |
| "title": "DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Monday ; Heyan", |
| "suffix": "" |
| }, |
| { |
| "first": "Chong", |
| "middle": [], |
| "last": "Huang", |
| "suffix": "" |
| }, |
| { |
| "first": "Qiang", |
| "middle": [], |
| "last": "Feng", |
| "suffix": "" |
| }, |
| { |
| "first": "Jiahui", |
| "middle": [], |
| "last": "Zhou", |
| "suffix": "" |
| }, |
| { |
| "first": "Xiong", |
| "middle": [], |
| "last": "Gu", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Gao", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "30 Entropy Converges Between Dialogue Participants: Explanations from an Information-Theoretic Perspective Yang Xu and David Reitter", |
| "volume": "16", |
| "issue": "", |
| "pages": "50--67", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Monday, August 8, 2016 (continued) Session 3B: Sentence vectors 15:30-15:50 Neural Summarization by Extracting Sentences and Words Jianpeng Cheng and Mirella Lapata 16:10-16:30 Neural Networks For Negation Scope Detection Federico Fancellu, Adam Lopez and Bonnie Webber 16:30-16:50 CSE: Conceptual Sentence Embeddings based on Attention Model Yashen Wang, Heyan Huang, Chong Feng, Qiang Zhou, Jiahui Gu and Xiong Gao Session 3C: Parsing III Session 3D: Dialog 15:30-15:50 DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstruc- tured Documents Zhao Yan, Nan Duan, Junwei Bao, Peng Chen, Ming Zhou, Zhoujun Li and Jianshe Zhou 15:50-16:10 Investigating the Sources of Linguistic Alignment in Conversation Gabriel Doyle and Michael C. Frank 16:10-16:30 Entropy Converges Between Dialogue Participants: Explanations from an Information-Theoretic Perspective Yang Xu and David Reitter 16:30-16:50 Finding the Middle Ground -A Model for Planning Satisficing Answers Sabine Janzen, Wolfgang Maa\u00df and Tobias Kowatsch 16:50-17:10 A Sentence Interaction Network for Modeling Dependence between Sentences Biao Liu and Minlie Huang xxxix", |
| "links": null |
| }, |
| "BIBREF42": { |
| "ref_id": "b42", |
| "title": "Easy Things First: Installments Improve Referring Expression Generation for Objects in Photographs Sina Zarrie\u00df and David Schlangen Session 3F: Entities and coreference 15:30-15:50 Collective Entity Resolution with Multi-Focal Attention Amir Globerson", |
| "authors": [ |
| { |
| "first": "Phil", |
| "middle": [], |
| "last": "Monday", |
| "suffix": "" |
| }, |
| { |
| "first": "Edward", |
| "middle": [], |
| "last": "Blunsom", |
| "suffix": "" |
| }, |
| { |
| "first": "Karl", |
| "middle": [ |
| "Moritz" |
| ], |
| "last": "Grefenstette", |
| "suffix": "" |
| }, |
| { |
| "first": "Tom\u00e1\u0161", |
| "middle": [], |
| "last": "Hermann", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Ko\u010disk\u00fd", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "50 Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric Nafise Sadat Moosavi and Michael Strube", |
| "volume": "15", |
| "issue": "", |
| "pages": "50--67", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Monday, August 8, (continued) Session 3E: Generation 15:30-15:50 Towards more variation in text generation: Developing and evaluating variation models for choice of referential form Thiago Castro Ferreira, Emiel Krahmer and Sander Wubben 15:50-16:10 How Much is 131 Million Dollars? Putting Numbers in Perspective with Composi- tional Descriptions Arun Chaganty and Percy Liang 16:10-16:30 Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus Iulian Vlad Serban, Alberto Garc\u00eda-Dur\u00e1n, Caglar Gulcehre, Sungjin Ahn, Sarath Chandar, Aaron Courville and Yoshua Bengio 16:30-16:50 Latent Predictor Networks for Code Generation Wang Ling, Phil Blunsom, Edward Grefenstette, Karl Moritz Hermann, Tom\u00e1\u0161 Ko\u010disk\u00fd, Fumin Wang and Andrew Senior 16:50-17:10 Easy Things First: Installments Improve Referring Expression Generation for Ob- jects in Photographs Sina Zarrie\u00df and David Schlangen Session 3F: Entities and coreference 15:30-15:50 Collective Entity Resolution with Multi-Focal Attention Amir Globerson, Nevena Lazic, Soumen Chakrabarti, Amarnag Subramanya, Michael Ringaard and Fernando Pereira 16:30-16:50 Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric Nafise Sadat Moosavi and Michael Strube 16:50-17:10 Improving Coreference Resolution by Learning Entity-Level Distributed Represen- tations Kevin Clark and Christopher D. Manning xl Monday, August 8, 2016 (continued) Session 3G: Topics 15:30-15:50 Effects of Creativity and Cluster Tightness on Short Text Clustering Performance Catherine Finegan-Dollak, Reed Coke, Rui Zhang, Xiangyi Ye and Dragomir Radev 15:50-16:10 Generative Topic Embedding: a Continuous Representation of Documents Shaohua Li, Tat-Seng Chua, Jun Zhu and Chunyan Miao 16:30-16:50 Detecting Common Discussion Topics Across Culture From News Reader Comments Bei Shi, Wai Lam, Lidong Bing and Yinqing Xu 16:50-17:10 A Discriminative Topic Model using Document Network Structure Weiwei Yang, Jordan Boyd-Graber and Philip Resnik", |
| "links": null |
| }, |
| "BIBREF43": { |
| "ref_id": "b43", |
| "title": "Simpler Context-Dependent Logical Forms via Model Projections Reginald Long", |
| "authors": [ |
| { |
| "first": "Tuesday", |
| "middle": [], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "20 Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text Kristina Toutanova", |
| "volume": "9", |
| "issue": "", |
| "pages": "20--31", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Tuesday, August 9, 2016 9:00-10:10 Invited talk II: Mark Steedman 10:10-10:40 Coffee break Session 4A: Relations and knowledge bases 10:40-11:00 Identifying Causal Relations Using Parallel Wikipedia Articles Christopher Hidey and Kathy McKeown 11:00-11:20 Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text Kristina Toutanova, Victoria Lin, Wen-tau Yih, Hoifung Poon and Chris Quirk 11:20-11:40 Commonsense Knowledge Base Completion Xiang Li, Aynaz Taheri, Lifu Tu and Kevin Gimpel Session 4B: Semantic parsing II 10:40-11:00 Simpler Context-Dependent Logical Forms via Model Projections Reginald Long, Panupong Pasupat and Percy Liang 11:20-11:40 A Fast Unified Model for Parsing and Sentence Understanding Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning and Christopher Potts xlvii", |
| "links": null |
| }, |
| "BIBREF44": { |
| "ref_id": "b44", |
| "title": "00 Beyond Plain Spatial Knowledge: Determining Where Entities Are and Are Not Located, and For How Long Alakananda Vempala and Eduardo Blanco", |
| "authors": [ |
| { |
| "first": "Tuesday ; Timothy", |
| "middle": [], |
| "last": "Baldwin", |
| "suffix": "" |
| }, |
| { |
| "first": "Jey", |
| "middle": [ |
| "Han" |
| ], |
| "last": "Lau", |
| "suffix": "" |
| }, |
| { |
| "first": "Diana", |
| "middle": [], |
| "last": "Mccarthy", |
| "suffix": "" |
| }, |
| { |
| "first": "Francis", |
| "middle": [], |
| "last": "Bond ; Denis Paperno", |
| "suffix": "" |
| }, |
| { |
| "first": "Germ\u00e1n", |
| "middle": [], |
| "last": "Kruszewski", |
| "suffix": "" |
| }, |
| { |
| "first": "Angeliki", |
| "middle": [], |
| "last": "Lazaridou", |
| "suffix": "" |
| }, |
| { |
| "first": "Ngoc", |
| "middle": [ |
| "Quan" |
| ], |
| "last": "Pham", |
| "suffix": "" |
| }, |
| { |
| "first": "Raffaella", |
| "middle": [], |
| "last": "Bernardi", |
| "suffix": "" |
| }, |
| { |
| "first": "Sandro", |
| "middle": [], |
| "last": "Pezzelle", |
| "suffix": "" |
| }, |
| { |
| "first": "Marco", |
| "middle": [], |
| "last": "Baroni", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change William L. Hamilton, Jure Leskovec and Dan Jurafsky Session 4D: Tasks and datasets", |
| "volume": "10", |
| "issue": "", |
| "pages": "0--13", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Tuesday, August 9, (continued) Session 4C: Word meaning II 11:20-11:40 Investigating Language Universal and Specific Properties in Word Embeddings Peng Qian, Xipeng Qiu and Xuanjing Huang 11:40-12:00 Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change William L. Hamilton, Jure Leskovec and Dan Jurafsky Session 4D: Tasks and datasets 10:40-11:00 Beyond Plain Spatial Knowledge: Determining Where Entities Are and Are Not Located, and For How Long Alakananda Vempala and Eduardo Blanco 11:00-11:20 LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribu- tion Learning Andrew Bennett, Timothy Baldwin, Jey Han Lau, Diana McCarthy and Francis Bond 11:20-11:40 The LAMBADA dataset: Word prediction requiring a broad discourse context Denis Paperno, Germ\u00e1n Kruszewski, Angeliki Lazaridou, Ngoc Quan Pham, Raf- faella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda and Raquel Fer- nandez 11:40-12:00 WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fan- drianto, Jay Han, Matthew Kelcey and David Berthelot Session 4E: Parsing IV 11:00-11:20 Optimizing Spectral Learning for Parsing Shashi Narayan and Shay B. Cohen 11:20-11:40 Stack-propagation: Improved Representation Learning for Syntax Yuan Zhang and David Weiss xlviii Tuesday, August 9, 2016 (continued) Session 4F: Document analysis 10:40-11:00 Inferring Perceived Demographics from User Emotional Tone and User- Environment Emotional Contrast Svitlana Volkova and Yoram Bachrach 11:00-11:20 Prototype Synthesis for Model Laws Matthew Burgess, Eugenia Giraudy and Eytan Adar 11:20-11:40 Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM Ivan Habernal and Iryna Gurevych 11:40-12:00 Discovery of Treatments from Text Corpora Christian Fong and Justin Grimmer 12:00-13:40 Lunch break Session 5A: Deep learning (short papers)", |
| "links": null |
| }, |
| "BIBREF45": { |
| "ref_id": "b45", |
| "title": "Session 5B: Semantics and generation", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Session 5B: Semantics and generation (short papers)", |
| "links": null |
| }, |
| "BIBREF46": { |
| "ref_id": "b46", |
| "title": "Session 5C: Machine translation II", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Session 5C: Machine translation II (short papers)", |
| "links": null |
| }, |
| "BIBREF48": { |
| "ref_id": "b48", |
| "title": "Graber and Hal Daum\u00e9 III Linguistic Benchmarks of Online News Article Quality Ioannis Arapakis, Filipa Peleja, Barla Berkant and Joao Magalhaes Alleviating Poor Context with Background Knowledge for Named Entity Disambiguation Ander Barrena, Aitor Soroa and Eneko Agirre Mining Paraphrasal Typed Templates from a Plain Text Corpus Or Biran, Terra Blevins and Kathleen McKeown How to Train Dependency Parsers with Inexact Search for Joint Sentence Boundary Detection and Parsing of Entire Documents Anders Bj\u00f6rkelund, Agnieszka Fale\u0144ska, Wolfgang Seeker and Jonas Kuhn MUTT: Metric Unit TesTing for Language Generation Tasks William Boag, Renan Campos, Kate Saenko and Anna Rumshisky N-gram language models for massively parallel devices Nikolay Bogoychev and Adam Lopez Cross-Lingual Morphological Tagging for Low-Resource Languages Jan Buys and Jan A. Botha Semi-Supervised Learning for Neural Machine Translation Yong", |
| "authors": [ |
| { |
| "first": "Julia", |
| "middle": [], |
| "last": "Nlp Artem Sokolov", |
| "suffix": "" |
| }, |
| { |
| "first": "Christopher", |
| "middle": [], |
| "last": "Kreutzer", |
| "suffix": "" |
| }, |
| { |
| "first": "Stefan Riezler ; Jianshu", |
| "middle": [], |
| "last": "Lo", |
| "suffix": "" |
| }, |
| { |
| "first": "Xiaodong", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "Jianfeng", |
| "middle": [], |
| "last": "He", |
| "suffix": "" |
| }, |
| { |
| "first": "Lihong", |
| "middle": [], |
| "last": "Gao", |
| "suffix": "" |
| }, |
| { |
| "first": "Li", |
| "middle": [], |
| "last": "Li", |
| "suffix": "" |
| }, |
| { |
| "first": "Mari", |
| "middle": [ |
| ";" |
| ], |
| "last": "Deng", |
| "suffix": "" |
| }, |
| { |
| "first": "Zhengdong", |
| "middle": [], |
| "last": "Gu", |
| "suffix": "" |
| }, |
| { |
| "first": "Hang", |
| "middle": [], |
| "last": "Lu", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Li", |
| "suffix": "" |
| }, |
| { |
| "first": "O", |
| "middle": [ |
| "K" |
| ], |
| "last": "Victor", |
| "suffix": "" |
| }, |
| { |
| "first": "Chris", |
| "middle": [], |
| "last": "Li ; Manaal Faruqui", |
| "suffix": "" |
| }, |
| { |
| "first": "Dan", |
| "middle": [], |
| "last": "Dyer", |
| "suffix": "" |
| }, |
| { |
| "first": ";", |
| "middle": [], |
| "last": "Roth", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Take", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Took", |
| "suffix": "" |
| }, |
| { |
| "first": "Goose", |
| "middle": [], |
| "last": "Gaggle", |
| "suffix": "" |
| }, |
| { |
| "first": "Read ; Yong", |
| "middle": [], |
| "last": "Book", |
| "suffix": "" |
| }, |
| { |
| "first": "Zhongjun", |
| "middle": [], |
| "last": "Cheng", |
| "suffix": "" |
| }, |
| { |
| "first": "Wei", |
| "middle": [], |
| "last": "He", |
| "suffix": "" |
| }, |
| { |
| "first": "Hua", |
| "middle": [], |
| "last": "He", |
| "suffix": "" |
| }, |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Wu ; Jianfu Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Warren ; Zhiting", |
| "suffix": "" |
| }, |
| { |
| "first": "Yuntian", |
| "middle": [], |
| "last": "Hu", |
| "suffix": "" |
| }, |
| { |
| "first": "Mrinmaya", |
| "middle": [], |
| "last": "Deng", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Sachan ; Ishan", |
| "suffix": "" |
| }, |
| { |
| "first": "Jacob", |
| "middle": [], |
| "last": "Misra", |
| "suffix": "" |
| }, |
| { |
| "first": "Margaret", |
| "middle": [], |
| "last": "Devlin", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Mitchell", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "10 Cross-domain Text Classification with Multiple Domains and Disparate Label Sets Himanshu Sharad Bhatt, Manjira Sinha and Shourya Roy Session 6B: Word vectors II", |
| "volume": "16", |
| "issue": "", |
| "pages": "0--15", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Session 5E: Potpourri I (short papers) 15:00-15:30 Coffee break Session 6A: Machine learning 15:30-15:50 Learning Structured Predictors from Bandit Feedback for Interactive NLP Artem Sokolov, Julia Kreutzer, Christopher Lo and Stefan Riezler 16:10-16:30 Deep Reinforcement Learning with a Natural Language Action Space Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng and Mari Ostendorf 16:30-16:50 Incorporating Copying Mechanism in Sequence-to-Sequence Learning Jiatao Gu, Zhengdong Lu, Hang Li and Victor O.K. Li 16:50-17:10 Cross-domain Text Classification with Multiple Domains and Disparate Label Sets Himanshu Sharad Bhatt, Manjira Sinha and Shourya Roy Session 6B: Word vectors II 15:50-16:10 Morphological Smoothing and Extrapolation of Word Embeddings Ryan Cotterell, Hinrich Sch\u00fctze and Jason Eisner 16:10-16:30 Cross-lingual Models of Word Embeddings: An Empirical Comparison Shyam Upadhyay, Manaal Faruqui, Chris Dyer and Dan Roth 16:30-16:50 Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning Ekaterina Vylomova, Laura Rimell, Trevor Cohn and Timothy Baldwin l Tuesday, August 9, 2016 (continued) Session 6C: Machine translation III 15:30-15:50 Minimum Risk Training for Neural Machine Translation Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun and Yang Liu 16:10-16:30 A Character-level Decoder without Explicit Segmentation for Neural Machine Translation Junyoung Chung, Kyunghyun Cho and Yoshua Bengio 16:30-16:50 Target-Side Context for Discriminative Models in Statistical Machine Translation Ale\u0161 Tamchyna, Alexander Fraser, Ond\u0159ej Bojar and Marcin Junczys-Dowmunt 16:50-17:10 Neural Machine Translation of Rare Words with Subword Units Rico Sennrich, Barry Haddow and Alexandra Birch Session 6D: Discourse 15:30-15:50 Implicit Discourse Relation Detection via a Deep Architecture with Gated Rele- vance Network Jifan Chen, Qi Zhang, Pengfei Liu, Xipeng Qiu and Xuanjing Huang 15:50-16:10 Model Architectures for Quotation Detection Christian Scheible, Roman Klinger and Sebastian Pad\u00f3 16:10-16:30 Speech Act Modeling of Written Asynchronous Conversations with Task-Specific Embeddings and Conditional Structured Models Shafiq Joty and Enamul Hoque 16:30-16:50 Situation entity types: automatic classification of clause-level aspect Annemarie Friedrich, Alexis Palmer and Manfred Pinkal Tuesday, August 9, (continued) Session 6E: Language and vision 15:30-15:50 Learning Prototypical Event Structure from Photo Albums Antoine Bosselut, Jianfu Chen, David Warren, Hannaneh Hajishirzi and Yejin Choi 15:50-16:10 Cross-Lingual Image Caption Generation Takashi Miyazaki and Nobuyuki Shimizu 16:10-16:30 Learning Concept Taxonomies from Multi-modal Data Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan and Eric Xing 16:30-16:50 Generating Natural Questions About an Image Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, Margaret Mitchell, Xiaodong He and Lucy Vanderwende 16:50-17:10 Physical Causality of Action Verbs in Grounded Language Understanding Qiaozi Gao, Malcolm Doering, Shaohua Yang and Joyce Chai Session 6F: Summarization 16:30-16:50 Optimizing an Approximation of ROUGE -a Problem-Reduction Approach to Ex- tractive Multi-Document Summarization Maxime Peyrard and Judith Eckle-Kohler Session 6G: Learner language 15:30-15:50 Phrase Structure Annotation and Parsing for Learner English Ryo Nagata and Keisuke Sakaguchi 15:50-16:10 A Trainable Spaced Repetition Model for Language Learning Burr Settles and Brendan Meeder 16:30-16:50 User Modeling in Language Learning with Macaronic Texts Adithya Renduchintala, Rebecca Knowles, Philipp Koehn and Jason Eisner 16:50-17:10 On the Similarities Between Native, Non-native and Translated Texts Ella Rabinovich, Sergiu Nisioi, Noam Ordan and Shuly Wintner Tuesday, August 9, 2016 (continued) 17:30-19:00 Poster and dinner session II Learning Text Pair Similarity with Context-sensitive Autoencoders Hadi Amiri, Philip Resnik, Jordan Boyd-Graber and Hal Daum\u00e9 III Linguistic Benchmarks of Online News Article Quality Ioannis Arapakis, Filipa Peleja, Barla Berkant and Joao Magalhaes Alleviating Poor Context with Background Knowledge for Named Entity Disam- biguation Ander Barrena, Aitor Soroa and Eneko Agirre Mining Paraphrasal Typed Templates from a Plain Text Corpus Or Biran, Terra Blevins and Kathleen McKeown How to Train Dependency Parsers with Inexact Search for Joint Sentence Boundary Detection and Parsing of Entire Documents Anders Bj\u00f6rkelund, Agnieszka Fale\u0144ska, Wolfgang Seeker and Jonas Kuhn MUTT: Metric Unit TesTing for Language Generation Tasks William Boag, Renan Campos, Kate Saenko and Anna Rumshisky N-gram language models for massively parallel devices Nikolay Bogoychev and Adam Lopez Cross-Lingual Morphological Tagging for Low-Resource Languages Jan Buys and Jan A. Botha Semi-Supervised Learning for Neural Machine Translation Yong Cheng, Wei Xu, Zhongjun He, Wei He, Hua Wu, Maosong Sun and Yang Liu Strategies for Training Large Vocabulary Neural Language Models Wenlin Chen, David Grangier and Michael Auli Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time Silvio Cordeiro, Carlos Ramisch, Marco Idiart and Aline Villavicencio Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints Greg Durrett, Taylor Berg-Kirkpatrick and Dan Klein Wednesday, August 10, 2016 9:00-9:40 President's talk 9:40-10:10 Coffee break Session 7A: Outstanding papers I 10:10-10:30 A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task Danqi Chen, Jason Bolton and Christopher D. Manning 10:30-10:50 Learning Language Games through Interaction Sida I. Wang, Percy Liang and Christopher D. Manning 10:50-11:10 Finding Non-Arbitrary Form-Meaning Systematicity Using String-Metric Learning for Kernel Regression E.Dario Gutierrez, Roger Levy and Benjamin Bergen 11:10-11:30 Improving Hypernymy Detection with an Integrated Path-based and Distributional Method Vered Shwartz, Yoav Goldberg and Ido Dagan Session 7B: Outstanding papers II 10:10-10:30 Multimodal Pivots for Image Caption Translation Julian Hitschler, Shigehiko Schamoni and Stefan Riezler 10:30-10:50 Harnessing Deep Neural Networks with Logic Rules Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy and Eric Xing 10:50-11:10 Case and Cause in Icelandic: Reconstructing Causal Networks of Cascaded Lan- guage Changes Fermin Moscoso del Prado Martin and Christian Brendel 11:10-11:30 On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Sys- tems Pei-Hao Su, Milica Gasic, Nikola Mrk\u0161i\u0107, Lina M. Rojas Barahona, Stefan Ultes, David Vandyke, Tsung-Hsien Wen and Steve Young Wednesday, August 10, (continued) 11:30-11:50 Globally Normalized Transition-Based Neural Networks Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessandro Presta, Kuzman Ganchev, Slav Petrov and Michael Collins 11:50-13:30 Lunch break 13:30-15:00 ACL business meeting (open to all) 15:00-15:30 Coffee break Session 8A: Question answering II (short papers)", |
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| "text": "Mark Steedman is Professor of Cognitive Science in the School of Informatics at the University of Edinburgh. Previously, he taught as Professor in the Department of Computer and Information Science at the University of Pennsylvania, which he joined as Associate Professor in 1988, after teaching at the Universities of Warwick and Edinburgh. His PhD is in Artificial Intelligence from the University of Edinburgh. He was a Alfred P. Sloan Fellow at the University of Texas at Austin in 1980/81, and a Visiting Professor at Penn in 1986/87. He is a Fellow of the American Association for Artificial Intelligence, the British Academy, the Royal Society of Edinburgh, the Association for Computational Linguistics, and the Cognitive Science Society, and a Member of the European Academy.", |
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| "text": "Noise reduction and targeted exploration in imitation learning for Abstract Meaning Representation parsing James Goodman, Andreas Vlachos and Jason Naradowsky . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Data Recombination for Neural Semantic Parsing Robin Jia and Percy Liang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning Andrew Bennett, Timothy Baldwin, Jey Han Lau, Diana McCarthy and Francis Bond . . . . . . . 1513 The LAMBADA dataset: Word prediction requiring a broad discourse context Denis Paperno, Germ\u00e1n Kruszewski, Angeliki Lazaridou, Ngoc Quan Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda and Raquel Fernandez . . . . . . . . . . . . . . . . . . . . . . . . . 1525" |
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