| { |
| "paper_id": "2020", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T12:41:42.791813Z" |
| }, |
| "title": "", |
| "authors": [ |
| { |
| "first": "Oren", |
| "middle": [], |
| "last": "Barkan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Frederic", |
| "middle": [], |
| "last": "Bechet", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Vitor", |
| "middle": [], |
| "last": "Carvalho", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Nicholas", |
| "middle": [], |
| "last": "Chamansingh", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Tobago", |
| "middle": [], |
| "last": "Praveen Chandar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Li", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Ido", |
| "middle": [], |
| "last": "Cohn", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Israel", |
| "middle": [], |
| "last": "Google", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Kristian", |
| "middle": [], |
| "last": "Hammond", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Derrick", |
| "middle": [], |
| "last": "Higgins", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Sanjeev", |
| "middle": [], |
| "last": "Kumar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Quark", |
| "middle": [], |
| "last": "Ai", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Varun", |
| "middle": [], |
| "last": "Kumar", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Amazon", |
| "middle": [], |
| "last": "Alexa", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Gakuto", |
| "middle": [], |
| "last": "Kurata", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Jennifer", |
| "middle": [ |
| "J" |
| ], |
| "last": "Liang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Alexander", |
| "middle": [], |
| "last": "Loeser", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Courtney", |
| "middle": [], |
| "last": "Mansfield", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Marie", |
| "middle": [], |
| "last": "Meteer", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Fabian", |
| "middle": [], |
| "last": "Suchanek", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Elena", |
| "middle": [], |
| "last": "Tutubalina", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Stephen", |
| "middle": [], |
| "last": "Wan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Csiro", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Yao", |
| "middle": [], |
| "last": "Australia", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Wan", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Huazhong", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Wei", |
| "middle": [], |
| "last": "Yang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Borealis", |
| "middle": [], |
| "last": "Ai", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| }, |
| { |
| "first": "Canada", |
| "middle": [ |
| "Jianguo" |
| ], |
| "last": "Zhang", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "Industry Track. This year marks the first in which COLING has a dedicated track for research related to computational linguistics deployed in real-world settings. In recent years, industrial research has been increasingly influential in the field of computational linguistics-both in the form of research departments that contribute to the advancement of computational linguistics, and also by way of the knowledgeable inventors and developers of innovative language and speech products. The goals of this session are to foster connections between industry practitioners, share insights from industry research to the broader community, and increase engagement with academia on research questions of high priority in industry. This session will showcase commercially-driven research from diverse angles, including the challenges of doing applied research at scale, production scalability, and a shifting data landscape. We received 124 submissions (79 long and 45 short) and had an acceptance rate of 23%. 1 Based on the first author's affiliation, an estimated 76% of submissions came from industry and 24% from academia. Geographically, most submissions were from North America (44%), 27-28% from Europe and Asia (respectively), and 1% from Africa. We thank the many people who have made this track a success. We are grateful to Donia Scott, general chair, for her support and for providing us with this opportunity. Thank you to program chairs N\u00faria Bel and Chengqing Zong; local chairs Leo Wanner, Horacio Saggion, and M\u00f3nica Dom\u00ednguez; publication chairs Derek Wong, Liang Huang, and Yang Zhao; web chairs Laura P\u00e9rez-Mayos and Amita Misra; virtual infrastructure chairs Paul Piwek, Llu\u00eds Padr\u00f3 Cirera, and Luis Espinosa Anke; publicity chairs Ghazaleh Kazeminejad, Tiejun Zhao, Ted Pedersen, and Anna Rogers; and all other members of the organizing committee. We were inspired by the success of the NAACL 2018 and 2019 industry tracks, and we thank Anastassia Loukin and the organizers of the NAACL 2019 Industry Track for their guidance. We are grateful to area chairs Juri Ganitkevitch and Greg Hanneman, and the program committee, whose dedication and hard work made this program possible.", |
| "pdf_parse": { |
| "paper_id": "2020", |
| "_pdf_hash": "", |
| "abstract": [ |
| { |
| "text": "Industry Track. This year marks the first in which COLING has a dedicated track for research related to computational linguistics deployed in real-world settings. In recent years, industrial research has been increasingly influential in the field of computational linguistics-both in the form of research departments that contribute to the advancement of computational linguistics, and also by way of the knowledgeable inventors and developers of innovative language and speech products. The goals of this session are to foster connections between industry practitioners, share insights from industry research to the broader community, and increase engagement with academia on research questions of high priority in industry. This session will showcase commercially-driven research from diverse angles, including the challenges of doing applied research at scale, production scalability, and a shifting data landscape. We received 124 submissions (79 long and 45 short) and had an acceptance rate of 23%. 1 Based on the first author's affiliation, an estimated 76% of submissions came from industry and 24% from academia. Geographically, most submissions were from North America (44%), 27-28% from Europe and Asia (respectively), and 1% from Africa. We thank the many people who have made this track a success. We are grateful to Donia Scott, general chair, for her support and for providing us with this opportunity. Thank you to program chairs N\u00faria Bel and Chengqing Zong; local chairs Leo Wanner, Horacio Saggion, and M\u00f3nica Dom\u00ednguez; publication chairs Derek Wong, Liang Huang, and Yang Zhao; web chairs Laura P\u00e9rez-Mayos and Amita Misra; virtual infrastructure chairs Paul Piwek, Llu\u00eds Padr\u00f3 Cirera, and Luis Espinosa Anke; publicity chairs Ghazaleh Kazeminejad, Tiejun Zhao, Ted Pedersen, and Anna Rogers; and all other members of the organizing committee. We were inspired by the success of the NAACL 2018 and 2019 industry tracks, and we thank Anastassia Loukin and the organizers of the NAACL 2019 Industry Track for their guidance. We are grateful to area chairs Juri Ganitkevitch and Greg Hanneman, and the program committee, whose dedication and hard work made this program possible.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Abstract", |
| "sec_num": null |
| } |
| ], |
| "body_text": [], |
| "back_matter": [], |
| "bib_entries": { |
| "BIBREF0": { |
| "ref_id": "b0", |
| "title": "Evaluating Cross-Lingual Transfer Learning Approaches in Multilingual Conversational Agent Models Lizhen", |
| "authors": [ |
| { |
| "first": "Olga", |
| "middle": [], |
| "last": "Tan", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "Golovneva", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Evaluating Cross-Lingual Transfer Learning Approaches in Multilingual Conversational Agent Models Lizhen Tan and Olga Golovneva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1", |
| "links": null |
| }, |
| "BIBREF1": { |
| "ref_id": "b1", |
| "title": "Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems Shailza Jolly, Tobias Falke, Caglar Tirkaz and Daniil Sorokin", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Fea- tures in Task-Oriented Dialog Systems Shailza Jolly, Tobias Falke, Caglar Tirkaz and Daniil Sorokin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10", |
| "links": null |
| }, |
| "BIBREF2": { |
| "ref_id": "b2", |
| "title": "Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances Tobias Falke, Markus Boese, Daniil Sorokin, Caglar Tirkaz and", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances Tobias Falke, Markus Boese, Daniil Sorokin, Caglar Tirkaz and Patrick Lehnen . . . . . . . . . . . . . . . 21", |
| "links": null |
| }, |
| "BIBREF3": { |
| "ref_id": "b3", |
| "title": "Query Distillation: BERT-based Distillation for Ensemble Ranking Wangshu Zhang", |
| "authors": [ |
| { |
| "first": "Junhong", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| }, |
| { |
| "first": "Zujie", |
| "middle": [], |
| "last": "Wen", |
| "suffix": "" |
| }, |
| { |
| "first": "Yafang", |
| "middle": [], |
| "last": "Wang", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". . . . . . . . . . . . ." |
| ], |
| "last": "Gerard De Melo", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Query Distillation: BERT-based Distillation for Ensemble Ranking Wangshu Zhang, Junhong Liu, Zujie Wen, Yafang Wang and Gerard de Melo . . . . . . . . . . . . . . . . . 33", |
| "links": null |
| }, |
| "BIBREF4": { |
| "ref_id": "b4", |
| "title": "Semantic Diversity for Natural Language Understanding Evaluation in Dialog Systems Enrico Palumbo", |
| "authors": [], |
| "year": null, |
| "venue": "Andrea Mezzalira", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Semantic Diversity for Natural Language Understanding Evaluation in Dialog Systems Enrico Palumbo, Andrea Mezzalira, Cristina Marco, Alessandro Manzotti and Daniele Amberti 44", |
| "links": null |
| }, |
| "BIBREF5": { |
| "ref_id": "b5", |
| "title": "An Empirical Study on Multi-Task Learning for Text Style Transfer and Paraphrase Generation Pawel Bujnowski", |
| "authors": [ |
| { |
| "first": "Kseniia", |
| "middle": [], |
| "last": "Ryzhova", |
| "suffix": "" |
| }, |
| { |
| "first": "Hyungtak", |
| "middle": [], |
| "last": "Choi", |
| "suffix": "" |
| }, |
| { |
| "first": "Katarzyna", |
| "middle": [], |
| "last": "Witkowska", |
| "suffix": "" |
| }, |
| { |
| "first": "Jaroslaw", |
| "middle": [], |
| "last": "Piersa", |
| "suffix": "" |
| }, |
| { |
| "first": "Tymoteusz", |
| "middle": [], |
| "last": "Krumholc", |
| "suffix": "" |
| }, |
| { |
| "first": "Katarzyna", |
| "middle": [], |
| "last": "Beksa", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "An Empirical Study on Multi-Task Learning for Text Style Transfer and Paraphrase Generation Pawel Bujnowski, Kseniia Ryzhova, Hyungtak Choi, Katarzyna Witkowska, Jaroslaw Piersa, Ty- moteusz Krumholc and Katarzyna Beksa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50", |
| "links": null |
| }, |
| "BIBREF6": { |
| "ref_id": "b6", |
| "title": "Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data Ankit Arun", |
| "authors": [ |
| { |
| "first": "Soumya", |
| "middle": [], |
| "last": "Batra", |
| "suffix": "" |
| }, |
| { |
| "first": "Vikas", |
| "middle": [], |
| "last": "Bhardwaj", |
| "suffix": "" |
| }, |
| { |
| "first": "Ashwini", |
| "middle": [], |
| "last": "Challa", |
| "suffix": "" |
| }, |
| { |
| "first": "Pinar", |
| "middle": [], |
| "last": "Donmez", |
| "suffix": "" |
| }, |
| { |
| "first": "Peyman", |
| "middle": [], |
| "last": "Heidari", |
| "suffix": "" |
| }, |
| { |
| "first": "Hakan", |
| "middle": [], |
| "last": "Inan", |
| "suffix": "" |
| }, |
| { |
| "first": "Shashank", |
| "middle": [], |
| "last": "Jain", |
| "suffix": "" |
| }, |
| { |
| "first": "Anuj", |
| "middle": [], |
| "last": "Kumar", |
| "suffix": "" |
| }, |
| { |
| "first": "Shawn", |
| "middle": [], |
| "last": "Mei", |
| "suffix": "" |
| }, |
| { |
| "first": "Karthik", |
| "middle": [], |
| "last": "Mohan", |
| "suffix": "" |
| }, |
| { |
| "first": "Michael", |
| "middle": [ |
| ". . . ." |
| ], |
| "last": "White", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Peyman Heidari, Hakan Inan, Shashank Jain, Anuj Kumar, Shawn Mei, Karthik Mohan and Michael White . . . . . . . . . . 64", |
| "links": null |
| }, |
| "BIBREF7": { |
| "ref_id": "b7", |
| "title": "Interactive Question Clarification in Dialogue via Reinforcement Learning Xiang Hu", |
| "authors": [ |
| { |
| "first": "Zujie", |
| "middle": [], |
| "last": "Wen", |
| "suffix": "" |
| }, |
| { |
| "first": "Yafang", |
| "middle": [], |
| "last": "Wang", |
| "suffix": "" |
| }, |
| { |
| "first": "Xiaolong", |
| "middle": [], |
| "last": "Li", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". ." |
| ], |
| "last": "Gerard De Melo", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Interactive Question Clarification in Dialogue via Reinforcement Learning Xiang Hu, Zujie Wen, Yafang Wang, Xiaolong Li and Gerard de Melo . . . . . . . . . . . . . . . . . . . . . . . 78", |
| "links": null |
| }, |
| "BIBREF8": { |
| "ref_id": "b8", |
| "title": "Towards building a Robust Industry-scale Question Answering System Rishav Chakravarti", |
| "authors": [ |
| { |
| "first": "Anthony", |
| "middle": [], |
| "last": "Ferritto", |
| "suffix": "" |
| }, |
| { |
| "first": "Bhavani", |
| "middle": [], |
| "last": "Iyer", |
| "suffix": "" |
| }, |
| { |
| "first": "Lin", |
| "middle": [], |
| "last": "Pan", |
| "suffix": "" |
| }, |
| { |
| "first": "Radu", |
| "middle": [], |
| "last": "Florian", |
| "suffix": "" |
| }, |
| { |
| "first": "Salim", |
| "middle": [], |
| "last": "Roukos", |
| "suffix": "" |
| }, |
| { |
| "first": "Avi", |
| "middle": [], |
| "last": "Sil", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Towards building a Robust Industry-scale Question Answering System Rishav Chakravarti, Anthony Ferritto, Bhavani Iyer, Lin Pan, Radu Florian, Salim Roukos and Avi Sil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90", |
| "links": null |
| }, |
| "BIBREF10": { |
| "ref_id": "b10", |
| "title": "Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hypotheses with Hierarchical Attention Mingda Li", |
| "authors": [ |
| { |
| "first": "Xinyue", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| }, |
| { |
| "first": "Weitong", |
| "middle": [], |
| "last": "Ruan", |
| "suffix": "" |
| }, |
| { |
| "first": "Luca", |
| "middle": [], |
| "last": "Soldaini", |
| "suffix": "" |
| }, |
| { |
| "first": "Wael", |
| "middle": [], |
| "last": "Hamza", |
| "suffix": "" |
| }, |
| { |
| "first": "Chengwei", |
| "middle": [ |
| ". . ." |
| ], |
| "last": "Su", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hypotheses with Hierar- chical Attention Mingda Li, Xinyue Liu, Weitong Ruan, Luca Soldaini, Wael Hamza and Chengwei Su . . . . . . . 113", |
| "links": null |
| }, |
| "BIBREF11": { |
| "ref_id": "b11", |
| "title": "Misspelling Detection from Noisy Product Images Varun Nagaraj", |
| "authors": [ |
| { |
| "first": "Mingwei", |
| "middle": [], |
| "last": "Rao", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "Shen", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Misspelling Detection from Noisy Product Images Varun Nagaraj Rao and Mingwei Shen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124", |
| "links": null |
| }, |
| "BIBREF12": { |
| "ref_id": "b12", |
| "title": "Corpus of Hindi-English Code Mixed Sentences for Text Normalization Piyush Makhija", |
| "authors": [ |
| { |
| "first": "Ankit", |
| "middle": [], |
| "last": "Kumar", |
| "suffix": "" |
| }, |
| { |
| "first": "Anuj", |
| "middle": [], |
| "last": "Gupta", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "hinglishNorm -A Corpus of Hindi-English Code Mixed Sentences for Text Normalization Piyush Makhija, Ankit Kumar and Anuj Gupta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136", |
| "links": null |
| }, |
| "BIBREF13": { |
| "ref_id": "b13", |
| "title": "Assessing Social License to Operate from the Public Discourse on Social Media Chang Xu", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Assessing Social License to Operate from the Public Discourse on Social Media Chang Xu, Cecile Paris, Ross Sparks, Surya Nepal and Keith VanderLinden . . . . . . . . . . . . . . . . . 146", |
| "links": null |
| }, |
| "BIBREF14": { |
| "ref_id": "b14", |
| "title": "160 ix Scalable Cross-lingual Treebank Synthesis for Improved Production Dependency Parsers Yousef El", |
| "authors": [ |
| { |
| "first": "Samridhi", |
| "middle": [], |
| "last": "Sathyendra", |
| "suffix": "" |
| }, |
| { |
| "first": "Leah", |
| "middle": [], |
| "last": "Choudhary", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [ |
| ". . . . ." |
| ], |
| "last": "Nicolich-Henkin", |
| "suffix": "" |
| }, |
| { |
| "first": "Hiroshi", |
| "middle": [], |
| "last": "Kurdi", |
| "suffix": "" |
| }, |
| { |
| "first": "Efsun", |
| "middle": [], |
| "last": "Kanayama", |
| "suffix": "" |
| }, |
| { |
| "first": "Vittorio", |
| "middle": [], |
| "last": "Sarioglu Kayi", |
| "suffix": "" |
| }, |
| { |
| "first": "Todd", |
| "middle": [], |
| "last": "Castelli", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Ward", |
| "suffix": "" |
| }, |
| { |
| "first": ".", |
| "middle": [ |
| "." |
| ], |
| "last": "Radu Florian", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "Extreme Model Compression for On-device Natural Language Understanding Kanthashree Mysore", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Extreme Model Compression for On-device Natural Language Understanding Kanthashree Mysore Sathyendra, Samridhi Choudhary and Leah Nicolich-Henkin . . . . . . . . . . . 160 ix Scalable Cross-lingual Treebank Synthesis for Improved Production Dependency Parsers Yousef El-Kurdi, Hiroshi Kanayama, Efsun Sarioglu Kayi, Vittorio Castelli, Todd Ward and Radu Florian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172", |
| "links": null |
| }, |
| "BIBREF15": { |
| "ref_id": "b15", |
| "title": "An Industry Evaluation of Embedding-based Entity Alignment Ziheng Zhang", |
| "authors": [ |
| { |
| "first": "Hualuo", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| }, |
| { |
| "first": "Jiaoyan", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "Xi", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "Bo", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "YueJia Xiang and Yefeng Zheng", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "An Industry Evaluation of Embedding-based Entity Alignment Ziheng Zhang, Hualuo Liu, Jiaoyan Chen, Xi Chen, Bo Liu, YueJia Xiang and Yefeng Zheng . 179", |
| "links": null |
| }, |
| "BIBREF16": { |
| "ref_id": "b16", |
| "title": "Learning Domain Terms -Empirical Methods to Enhance Enterprise Text Analytics Performance Gargi Roy, Lipika Dey, Mohammad Shakir and Tirthankar Dasgupta", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Learning Domain Terms -Empirical Methods to Enhance Enterprise Text Analytics Performance Gargi Roy, Lipika Dey, Mohammad Shakir and Tirthankar Dasgupta . . . . . . . . . . . . . . . . . . . . . . . . 190", |
| "links": null |
| }, |
| "BIBREF17": { |
| "ref_id": "b17", |
| "title": "Model-agnostic Methods for Text Classification with Inherent Noise Kshitij Tayal, Rahul Ghosh and Vipin Kumar", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Model-agnostic Methods for Text Classification with Inherent Noise Kshitij Tayal, Rahul Ghosh and Vipin Kumar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202", |
| "links": null |
| }, |
| "BIBREF18": { |
| "ref_id": "b18", |
| "title": "Scoping Task Relevant Sentences in Documents Barun Patra, Vishwas Suryanarayanan, Chala Fufa, Pamela Bhattacharya and Charles Lee", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Scopeit", |
| "suffix": "" |
| } |
| ], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "ScopeIt: Scoping Task Relevant Sentences in Documents Barun Patra, Vishwas Suryanarayanan, Chala Fufa, Pamela Bhattacharya and Charles Lee . . . . 214", |
| "links": null |
| }, |
| "BIBREF19": { |
| "ref_id": "b19", |
| "title": "Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks Zhengyuan Liu, Pavitra Krishnaswamy, Ai Ti Aw and Nancy Chen . . . . . . . . . . . . . . . . . . . . . . . . . 228", |
| "links": null |
| }, |
| "BIBREF20": { |
| "ref_id": "b20", |
| "title": "Regularized Graph Convolutional Networks for Short Text Classification Kshitij Tayal", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Regularized Graph Convolutional Networks for Short Text Classification Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian and Vipin Kumar . . 236", |
| "links": null |
| }, |
| "BIBREF21": { |
| "ref_id": "b21", |
| "title": ":12 Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Peyman Heidari", |
| "authors": [ |
| { |
| "first": "Tuesday ; Junhong", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| }, |
| { |
| "first": "Zujie", |
| "middle": [], |
| "last": "Wen", |
| "suffix": "" |
| }, |
| { |
| "first": "Yafang", |
| "middle": [], |
| "last": "Wang", |
| "suffix": "" |
| }, |
| { |
| "first": "Gerard", |
| "middle": [], |
| "last": "De ; Andrea Mezzalira", |
| "suffix": "" |
| }, |
| { |
| "first": "Cristina", |
| "middle": [], |
| "last": "Marco", |
| "suffix": "" |
| }, |
| { |
| "first": "Alessandro", |
| "middle": [], |
| "last": "Manzotti", |
| "suffix": "" |
| }, |
| { |
| "first": "Daniele Amberti Wednesday ; Kseniia", |
| "middle": [], |
| "last": "Ryzhova", |
| "suffix": "" |
| }, |
| { |
| "first": "Hyungtak", |
| "middle": [], |
| "last": "Choi", |
| "suffix": "" |
| }, |
| { |
| "first": "Katarzyna", |
| "middle": [], |
| "last": "Witkowska", |
| "suffix": "" |
| }, |
| { |
| "first": "Jaroslaw", |
| "middle": [], |
| "last": "Piersa", |
| "suffix": "" |
| } |
| ], |
| "year": 2020, |
| "venue": "12 Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems Shailza Jolly, Tobias Falke", |
| "volume": "16", |
| "issue": "", |
| "pages": "30--46", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Tuesday, December 8, 2020 (UTC+1) 16:00-16:30 Session Industry 1: Dialogue 16:00-16:06 Evaluating Cross-Lingual Transfer Learning Approaches in Multilingual Conver- sational Agent Models Lizhen Tan and Olga Golovneva 16:06-16:12 Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems Shailza Jolly, Tobias Falke, Caglar Tirkaz and Daniil Sorokin 16:12-16:18 Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Col- lect Annotations For Long-Tail Utterances Tobias Falke, Markus Boese, Daniil Sorokin, Caglar Tirkaz and Patrick Lehnen 16:18-16:24 Query Distillation: BERT-based Distillation for Ensemble Ranking Wangshu Zhang, Junhong Liu, Zujie Wen, Yafang Wang and Gerard de Melo 16:24-16:30 Semantic Diversity for Natural Language Understanding Evaluation in Dialog Sys- tems Enrico Palumbo, Andrea Mezzalira, Cristina Marco, Alessandro Manzotti and Daniele Amberti Wednesday, December 9, 2020 (UTC+1) 16:00-16:30 Session Industry 2: Generation and Question Answering 16:00-16:06 An Empirical Study on Multi-Task Learning for Text Style Transfer and Paraphrase Generation Pawel Bujnowski, Kseniia Ryzhova, Hyungtak Choi, Katarzyna Witkowska, Jaroslaw Piersa, Tymoteusz Krumholc and Katarzyna Beksa 16:06-16:12 Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Pey- man Heidari, Hakan Inan, Shashank Jain, Anuj Kumar, Shawn Mei, Karthik Mohan and Michael White 16:12-16:18 Interactive Question Clarification in Dialogue via Reinforcement Learning Xiang Hu, Zujie Wen, Yafang Wang, Xiaolong Li and Gerard de Melo 16:18-16:24 Towards building a Robust Industry-scale Question Answering System Rishav Chakravarti, Anthony Ferritto, Bhavani Iyer, Lin Pan, Radu Florian, Salim Roukos and Avi Sil xi Wednesday, December 9, 2020 (UTC+1) (continued) 16:24-16:30 Delexicalized Paraphrase Generation Boya Yu, Konstantine Arkoudas and Wael Hamza Thursday, December 10, 2020 (UTC+1) 16:00-16:33 Session Industry 3: Applications 16:00-16:06 Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hy- potheses with Hierarchical Attention Mingda Li, Xinyue Liu, Weitong Ruan, Luca Soldaini, Wael Hamza and Chengwei Su 16:06-16:12 Misspelling Detection from Noisy Product Images Varun Nagaraj Rao and Mingwei Shen 16:12-16:18 hinglishNorm -A Corpus of Hindi-English Code Mixed Sentences for Text Normal- ization Piyush Makhija, Ankit Kumar and Anuj Gupta 16:18-16:24 Assessing Social License to Operate from the Public Discourse on Social Media Chang Xu, Cecile Paris, Ross Sparks, Surya Nepal and Keith VanderLinden 16:24-16:30 Extreme Model Compression for On-device Natural Language Understanding Kanthashree Mysore Sathyendra, Samridhi Choudhary and Leah Nicolich-Henkin 16:30-16:33 Scalable Cross-lingual Treebank Synthesis for Improved Production Dependency Parsers Yousef El-Kurdi, Hiroshi Kanayama, Efsun Sarioglu Kayi, Vittorio Castelli, Todd Ward and Radu Florian xii", |
| "links": null |
| }, |
| "BIBREF22": { |
| "ref_id": "b22", |
| "title": ":12 Learning Domain Terms -Empirical Methods to Enhance Enterprise Text Analytics Performance Gargi Roy, Lipika Dey", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [], |
| "last": "Friday ; Hualuo", |
| "suffix": "" |
| }, |
| { |
| "first": "Jiaoyan", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| }, |
| { |
| "first": "Xi", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "Bo", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Liu", |
| "suffix": "" |
| } |
| ], |
| "year": 2020, |
| "venue": "27 Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks Zhengyuan Liu", |
| "volume": "16", |
| "issue": "", |
| "pages": "27--43", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Friday, December 11, 2020 (UTC+1) 16:00-16:30 Session Industry 4: Machine Learning Applications 16:00-16:06 An Industry Evaluation of Embedding-based Entity Alignment Ziheng Zhang, Hualuo Liu, Jiaoyan Chen, Xi Chen, Bo Liu, YueJia Xiang and Yefeng Zheng 16:06-16:12 Learning Domain Terms -Empirical Methods to Enhance Enterprise Text Analytics Performance Gargi Roy, Lipika Dey, Mohammad Shakir and Tirthankar Dasgupta 16:12-16:18 Model-agnostic Methods for Text Classification with Inherent Noise Kshitij Tayal, Rahul Ghosh and Vipin Kumar 16:18-16:24 ScopeIt: Scoping Task Relevant Sentences in Documents Barun Patra, Vishwas Suryanarayanan, Chala Fufa, Pamela Bhattacharya and Charles Lee 16:24-16:27 Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks Zhengyuan Liu, Pavitra Krishnaswamy, Ai Ti Aw and Nancy Chen 16:27-16:30 Regularized Graph Convolutional Networks for Short Text Classification Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian and Vipin Kumar xiii", |
| "links": null |
| } |
| }, |
| "ref_entries": {} |
| } |
| } |
