Kayo Yin among many LTI researchers featured at prestigious conference

Tuesday, August 3, 2021 - by Bryan Burtner

Kayo Yin, a student in the LTI's Master of Language Technologies program, was honored with the Best Theme Paper designation at this year's Joint Conference of the 59th Meeting of the Association for Computational Linguistics and the 11th Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). Yin is the lead author of the paper Including Signed Languages in Natural Language Processing, which seeks to expand the usage of powerful tools and techniques from the field of Natural Language Processing into the realm of signed languages, the primary means of extemporaneous communication for many of the world's deaf and hard of hearing individuals. Per the paper's abstract, Yin and her co-authors "[call] on the NLP community to include signed languages as a research area with high social and scientific impact."

ACL-IJCNLP 2021 takes place from Monday, August 2 through Thursday, August 5 in Bangkok, Thailand. Together, the combined meetings serve as two of the premier conferences worldwide in the fields of Computational Linguistics and Natural Language Processing. The theme track of this year's conferences is NLP for Social Good. 

Along with Yin, a number of LTI researchers were honored by having their papers accepted by the conferences. Accepted papers with LTI authors are as follows:

Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis
Ruifan Li, Hao Chen, Fangxiang Feng, Zhanyu Ma, Xiaojie WANG and Eduard Hovy

Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data
Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nick Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov and Louis-Philippe Morency

Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network
Justin Lovelace, Denis Newman-Griffis, Shikhar Vashishth, Jill Fain Lehman and Carolyn Rosé

Including Signed Languages in Natural Language Processing
Kayo Yin, Amit Moryossef, Julie Hochgesang, Yoav Goldberg and Malihe Alikhani

Measuring and Increasing Context Usage in Context-Aware Machine Translation
Patrick Fernandes, Kayo Yin, Graham Neubig and André F. T. Martins

Do Context-Aware Translation Models Pay the Right Attention?
Kayo Yin, Patrick Fernandes, Danish Pruthi, Aditi Chaudhary, André F. T. Martins and Graham Neubig

A Survey of Race, Racism, and Anti-Racism in NLP
Anjalie Field, Su Lin Blodgett, Zeerak Waseem and Yulia Tsvetkov

CitationIE: Leveraging the Citation Graph for Scientific Information Extraction
Vijay Viswanathan, Graham Neubig and Pengfei Liu

Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
Abhilasha Ravichander, Alan W Black, Thomas Norton, Shomir Wilson and Norman Sadeh

Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding
Dongyeop Kang and Eduard Hovy

SpanNER: Named Entity Re-/Recognition as Span Prediction
Jinlan Fu, Xuanjing Huang and Pengfei Liu

Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques
Kundan Krishna, Sopan Khosla, Jeffrey Bigham and Zachary C. Lipton

More Identifiable yet Equally Performant Transformers for Text Classification
Rishabh Bhardwaj, Navonil Majumder, Soujanya Poria and Eduard Hovy

Machine Translation into Low-resource Language Varieties
Sachin Kumar, Antonios Anastasopoulos, Shuly Wintner and Yulia Tsvetkov

SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization
Yixin Liu and Pengfei Liu

Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Varun Gangal, Harsh Jhamtani, Eduard Hovy and Taylor Berg-Kirkpatrick

Could you give me a hint ? Generating inference graphs for defeasible reasoning
Aman Madaan, Dheeraj Rajagopal, Niket Tandon, Yiming Yang and Eduard Hovy

A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy

For More Information, Contact:

Bryan Burtner | bburtner@cs.cmu.edu | 412-268-2805