EMNLP

Biomedical Event Extraction with Hierarchical Knowledge Graphs

Kung-Hsiang Huang, Mu Yang, Nanyun Peng

Comments 8 pages, 3 figures, Findings of EMNLP 2020 (short)

AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network

Xinyu Wang, Yong Jiang, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu

Comments Accept to Main Conference of EMNLP 2020 (Short). Camera-ready, 8 Pages

Relation of the Relations: A New Paradigm of the Relation Extraction Problem

Zhijing Jin, Yongyi Yang, Xipeng Qiu, Zheng Zhang

Comments Passed the reviews of EMNLP; withdrawn for non-technical reasons

Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation

Nithin Holla, Pushkar Mishra, Helen Yannakoudakis, Ekaterina Shutova

Comments Camera-ready: Findings of EMNLP

The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures

Haim Dubossarsky, Ivan Vulić, Roi Reichart, Anna Korhonen

Comments EMNLP 2020: Long paper

A Sentiment-Controllable Topic-to-Essay Generator with Topic Knowledge Graph

Lin Qiao, Jianhao Yan, Fandong Meng, Zhendong Yang, Jie Zhou

Comments Accepted as a regular paper in Findings of EMNLP 2020

COGS: A Compositional Generalization Challenge Based on Semantic Interpretation

Najoung Kim, Tal Linzen

Comments Accepted to EMNLP 2020

OCNLI: Original Chinese Natural Language Inference

Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kuebler, Lawrence S. Moss

Comments Findings of EMNLP 2020

VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles

Mingzhe Li, Xiuying Chen, Shen Gao, Zhangming Chan, Dongyan Zhao, Rui Yan

Comments Accepted by The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)

Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis

Roy Bar-Haim, Yoav Kantor, Lilach Eden, Roni Friedman, Dan Lahav, Noam Slonim

Comments EMNLP 2020

Learning Which Features Matter: RoBERTa Acquires a Preference for Linguistic Generalizations (Eventually)

Alex Warstadt, Yian Zhang, Haau-Sing Li, Haokun Liu, Samuel R. Bowman

Comments accepted at EMNLP 2020

We Can Detect Your Bias: Predicting the Political Ideology of News Articles

Ramy Baly, Giovanni Da San Martino, James Glass, Preslav Nakov

Comments Political bias, bias in news, neural networks bias, adversarial adaptation, triplet loss, transformers, recurrent neural networks

Journal ref EMNLP-2020

InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction

Hansi Hettiarachchi, Tharindu Ranasinghe

Comments Accepted to the 6th Workshop on Noisy User-generated Text (W-NUT) at EMNLP 2020

Multilingual Offensive Language Identification with Cross-lingual Embeddings

Tharindu Ranasinghe, Marcos Zampieri

Comments Accepted to EMNLP 2020

Weakly Supervised Medication Regimen Extraction from Medical Conversations

Dhruvesh Patel, Sandeep Konam, Sai P. Selvaraj

Comments To appear in the Proceedings of the Clinical Natural Language Processing Workshop, EMNLP, 2020

Towards Accurate and Reliable Energy Measurement of NLP Models

Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian

Comments Accepted to SustaiNLP 2020 (co-located with EMNLP 2020)

End to End Binarized Neural Networks for Text Classification

Harshil Jain, Akshat Agarwal, Kumar Shridhar, Denis Kleyko

Comments 14 pages. Accepted at the SustaiNLP Workshop on Simple and Efficient Natural Language Processing at EMNLP 2020

Detecting Foodborne Illness Complaints in Multiple Languages Using English Annotations Only

Ziyi Liu, Giannis Karamanolakis, Daniel Hsu, Luis Gravano

Comments Accepted for the 11th International Workshop on Health Text Mining and Information Analysis (LOUHI@EMNLP 2020)

Learning Adaptive Language Interfaces through Decomposition

Siddharth Karamcheti, Dorsa Sadigh, Percy Liang

Comments Accepted at the 1st Workshop for Interactive and Executable Semantic Parsing (IntEx-SemPar) @ EMNLP 2020. 11 pages, 5 figures

PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation

Xiang Yue, Shuang Zhou

Comments Accepted by The 3rd ClinicalNLP Workshop at EMNLP'20

Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task

Dongyeop Kang, Eduard Hovy

Comments EMNLP 2020

Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions

Dongyeop Kang, Andrew Head, Risham Sidhu, Kyle Lo, Daniel S. Weld, Marti A. Hearst

Comments Workshop on Scholarly Document Processing (SDP), EMNLP 2020

Hierarchical Evidence Set Modeling for Automated Fact Extraction and Verification

Shyam Subramanian, Kyumin Lee

Comments 12 pages, 7 figures. Accepted to EMNLP 2020

On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks

Stephen Mussmann, Robin Jia, Percy Liang

Comments In Findings of EMNLP 2020

Semi-supervised Formality Style Transfer using Language Model Discriminator and Mutual Information Maximization

Kunal Chawla, Diyi Yang

Comments EMNLP 2020 Findings

Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings

Prafull Prakash, Saurabh Kumar Shashidhar, Wenlong Zhao, Subendhu Rongali, Haidar Khan, Michael Kayser

Comments Accepted at EMNLP 2020 (Findings); 7 Pages

Beyond Language: Learning Commonsense from Images for Reasoning

Wanqing Cui, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng

Comments Accepted to EMNLP'20 Findings

FIND: Human-in-the-Loop Debugging Deep Text Classifiers

Piyawat Lertvittayakumjorn, Lucia Specia, Francesca Toni

Comments 17 pages including appendices; To appear at EMNLP 2020

An Empirical Investigation of Beam-Aware Training in Supertagging

Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon

Comments EMNLP Findings 2020 camera-ready. Code can be found at https://github.com/negrinho/beam_learn_supertagging

Latent Tree Learning with Ordered Neurons: What Parses Does It Produce?

Yian Zhang

Comments 6 pages, 3 figures, 3 tables, to appear in Proceedings of the 2020 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP