Difference between revisions of "Community/workshop/2019/program"
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| 10:00 || 10:30 || '''Coffee Break''' | | 10:00 || 10:30 || '''Coffee Break''' | ||
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− | | || || '''Keynote 1''' Chair: | + | | || || '''Keynote 1''' Chair: Jörg Tiedemann |
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| 10:30 || 11:30 || Barbara Plank: <i>Multi-Task and Continual Learning for Multi-Modal NLP</i> | | 10:30 || 11:30 || Barbara Plank: <i>Multi-Task and Continual Learning for Multi-Modal NLP</i> |
Revision as of 12:15, 9 September 2019
The First NLPL Workshop on Deep Learning for Natural Language Processing
Monday, September 30, 2019 | ||
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09:00 | 09:20 | Opening |
Session 1 Chair: Leon Derczynski | ||
09:20 | 09:40 | Timothee Mickus, Denis Paperno and Matthieu Constant: Mark my Word: A Sequence-to-Sequence Approach to Definition Modeling |
09:40 | 10:00 | Robin Kurtz, Daniel Roxbo and Marco Kuhlmann: Improving Semantic Dependency Parsing with Syntactic Features |
10:00 | 10:30 | Coffee Break |
Keynote 1 Chair: Jörg Tiedemann | ||
10:30 | 11:30 | Barbara Plank: Multi-Task and Continual Learning for Multi-Modal NLP |
Session 2 Chair: Sara Stymne | ||
11:30 | 11:50 | Andrey Kutuzov and Elizaveta Kuzmenko: To Lemmatize or Not to Lemmatize: How Word Normalisation Affects ELMo Performance in Word Sense Disambiguation |
11:50 | 12:10 | Samuel Rönnqvist, Jenna Kanerva, Tapio Salakoski and Filip Ginter: Is Multilingual BERT Fluent in Language Generation? |
12:10 | 12:30 | Vinit Ravishankar, Memduh Gökırmak, Lilja Øvrelid and Erik Velldal: Multilingual Probing of Contextual Sentence Encoders |
12:30 | 14:00 | Lunch Break |
Keynote 2 Chair: Filip Ginter | ||
14:00 | 15:00 | Jussi Karlgren: High-Dimensional Semantic Spaces and the Squinting Linguist |
15:00 | 15:30 | Coffee Break |
Session 3 Chair: Lilja Øvrelid | ||
15.30 | 15:50 | Nicolaj Filrup Rasmussen, Kristian Nørgaard Jensen, Marco Placenti and Thai Wang: Cross-Domain Sentiment Classification using Vector Embedded Domain Representations |
15:50 | 16:10 | Matthias Damaschk, Tillmann Dönicke and Florian Lux: Multiclass Text Classification on Unbalanced, Sparse and Noisy Data |
16:10 | 16:30 | Discussion and Closing |