Adobe Research at EMNLP 2021

November 8, 2021

In this EMNLP 2021 paper, the authors developed a new summarization model using deep neural networks that produce relevant sentence representations, which the model then uses to select which sentences to include in the output summary.

The Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) will be held from November 7 to 11, 2021 as a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation. EMNLP is one of the top research conferences on natural language processing. In recent years, deep learning approaches have made a significant impact at this conference.

There are nine Adobe co-authored papers at EMNLP 2021 on research topics ranging from question answering, image captioning, summarization, authoring assistants, event understanding, and much more. 
Many of the accepted papers are the outcome of research internships. Please check out the Adobe Research Careers website to learn more about internships and full-time career opportunities.

EMNLP 2021 conference – Adobe co-authored papers

Main conference papers

"It Doesn't Look Good for a Date": Transforming Critiques into Preferences for Conversational Recommendation Systems
Victor Bursztyn, Jennifer Healey, Nedim Lipka, Eunyee Koh, Doug Downey, Larry Birnbaum
AUTOSUMM: Automatic Model Creation for Text Summarization
Sharmila Reddy Nangi, Atharv Tyagi, Jay Mundra, Sagnik Mukherjee, Raj Snehal, Niyati Chhaya, Aparna Garimella
CLAUSEREC: A Clause Recommendation Framework for AI-aided Contract Authoring
Vinay Aggarwal, Aparna Garimella, Balaji Vasan Srinivasan, Anandhavelu N, Rajiv Jain
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning
Jian-guo Zhang, Trung Bui, Seunghyun Yoon, Xiang Chen, Zhiwei Liu, Congying Xia, Quan Hung Tran, Walter Chang, Philip Yu
IGA: An Intent-Guided Authoring Assistant
Simeng Sun, Wenlong Zhao, Varun Manjunatha, Rajiv Jain, Vlad Morariu, Franck Dernoncourt, Balaji Vasan Srinivasan, Mohit Iyyer
Learning Prototype Representations Across Few-Shot Tasks for Event Detection
Viet Lai, Franck Dernoncourt, Thien Huu Nguyen
StreamHover: Livestream Transcript Summarization and Annotation
Sangwoo Cho, Franck Dernoncourt, Tim Ganter, Trung Bui, Nedim Lipka, Walter Chang, Hailin Jin, Jonathan Brandt, Hassan Foroosh, Fei Liu

Findings papers

QACE: Asking Questions to Evaluate an Image Caption
Hwanhee Lee, Thomas Scialom, Seunghyun Yoon, Franck Dernoncourt, Kyomin Jung

Workshop papers

TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts.
Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt, Nazli Goharian
Presented at the New Frontiers in Summarization Workshop

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