COLING’2020 outstanding papers announcement
COLING’2020 has announced in the programme 16 papers that are deemed to be of outstanding quality. The selected papers are all on short-list for Best Paper, which will be revealed in the Closing Session. This is the complete list:
- 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
- Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task Learning.
Morteza Rohanian and Julian Hough
- Linguistic Profiling of a Neural Language Model.
Alessio Miaschi, Dominique Brunato, Felice Dell’Orletta and Giulia Venturi
- On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages.
Satwik Bhattamishra, Kabir Ahuja and Navin Goyal
- KeyGames: A Game Theoretic Approach to Automatic Keyphrase Extraction.
Arnav Saxena, Mudit Mangal and Goonjan Jain
- 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
- DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool.
Ernie Chang, Jeriah Caplinger, Alex Marin, Xiaoyu Shen and Vera Demberg
- Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning.
Jon Ander Campos, Kyunghyun Cho, Arantxa Otegi, Aitor Soroa, Eneko Agirre and Gorka Azkune
- Decolonising Speech and Language Technology.
- Breeding Gender-aware Direct Speech Translation Systems.
Marco Gaido, Beatrice Savoldi, Luisa Bentivogli, Matteo Negri and Marco Turchi
- Misspelling Detection from Noisy Product Images.
Varun Nagaraj Rao and Mingwei Shen
- Effective Use of Target-side Context for Neural Machine Translation.
Hideya Mino, Hitoshi Ito, Isao Goto, Ichiro Yamada and Takenobu Tokunaga
- Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation.
Bryan Eikema and Wilker Aziz
- GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion.
Ramit Sawhney, Arnav Wadhwa, Shivam Agarwal and Rajiv Ratn Shah
- A Neural Model for Aggregating Coreference Annotation in Crowdsourcing.
Maolin Li, Hiroya Takamura and Sophia Ananiadou
- Dual Supervision Framework for Relation Extraction with Distant Supervision and Human Annotation.
Woohwan Jung and Kyuseok Shim