Vol-3164
urn:nbn:de:0074-3164-4

Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

SDU 2022
Scientific Document Understanding 2022

Proceedings of the Workshop on Scientific Document Understanding
co-located with 36th AAAI Conference on Artificial Inteligence (AAAI 2022)

Remote, March 1, 2022.

Edited by

Amir Pouran Ben Veyseh *
Franck Dernoncourt **
Thien Huu Nguyen *
Walter Chang **
Viet Dack Lai *

* University of Oregon, Eugene, OR, USA

** Adobe Research, San Jose, CA, USA

Table of Contents

Summary: There were 33 papers submitted for peer-review to this workshop. Out of these, 17 papers were accepted in the research track and 14 were accepted in the shared-task track.

Session 1: Research Track

Neural Architectures for Biological Inter-Sentence Relation Extraction
Enrique Noriega-Atala, Peter M. Lovett, Clayton Morrison, Mihai Surdeanu
Coherence-based Second Chance Autoencoders for Document Understanding
Saria Goudarzvand, Gharib Gharibi, Yugyung Lee
Longitudinal Citation Prediction using Temporal Graph Neural Networks
Andreas Nugaard Holm, Barbara Plank, Dustin Wright, Isabelle Augenstein
Zero-Shot and Few-Shot Classification of Biomedical Articles in Context of the COVID-19 Pandemic
Simon Lupart, Benoit Favre, Vassilina Nikoulina, Salah Ait-Mokhtar
BAM: Benchmarking Argument Mining on Scientific Documents
Florian Ruosch, Cristina Sarasua, Abraham Bernstein
Fine-grained Intent Classification in the Legal Domain
Ankan Mullick, Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik, R Raghav
Domain Adaptive Pretraining for Multilingual Acronym Extraction
Usama Yaseen, Stefan Langer
TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets
Susie Xi Rao, Johannes Rausch, Peter Egger, Ce Zhang
Sequence Labeling for Citation Field Extractionfrom Cyrillic Script References
Igor Shapiro, Tarek Saier, Michael Färber
CABACE: Injecting Character Sequence Information and Domain Knowledge for Enhanced Acronym and Long-Form Extraction
Nithish Kannen, Divyanshu Sheth, Abhranil Chandra, Shubhraneel Pal
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification
Ashish Rana, Deepanshu Khanna, Tirthankar Ghosal, Muskaan Singh, Harpreet Singh, Prashant Singh Rana
Acronym Identification using Transformers and Flair Framework
Fazlourrahman Balouchzahi, Oxana Vitman, Hosahalli Lakshmaiah Shashirekha, Grigori Sidorov, Alexander Gelbukh
When to Use Which Neural Network? Finding the Right Neural Network Architecture for a Research Problem
Michael Färber, Nicolas Weber
BERTicsson: A Recommender System For Troubleshooting
Nuria Marzo I Grimalt, Serveh Shalmashi, Forough Yaghoubi, Leif Jonsson, Amir H. Payberah
ANACONDA: Adversarial training with iNtrust loss in ACrONym DisambiguAtion
Fei Xia, Bin Li, Yixuan Weng, Xiusheng Huang, Shizhu He
Extraction of Competing Models using Distant Supervision and Graph Ranking
Swayatta Daw, Vikram Pudi
T5 Encoder Based Acronym Disambiguation with Weak Supervision
Gwangho Song, Hongrae Lee, Kyuseok Shim
Applying Multi-Task Reading Comprehension in Acronym Disambiguation
Yunpeng Tai, Xiaoyu Zhang, Xuefeng Xi
ADBCMM : Acronym Disambiguation by Building Counterfactuals and Multilingual Mixing
Yixuan Weng, Fei Xia, Bin Li, Xiusheng Huang, Shizhu He
Deeper Clinical Document Understanding using Relation Extraction
Hasham Ul Haq, Veysel Kocaman, David Talby
PSG: Prompt-based Sequence Generation for Acronym Extraction
Bin Li, Fei Xia, Yixuan Weng, Bin Sun, Shutao Li, Xiusheng Huang
SimCLAD: A Simple Framework for Contrastive Learning of Acronym Disambiguation
Bin Li, Fei Xia, Yixuan Weng, Xiusheng Huang, Bin Sun
Scientific Chart Summarization: Datasets and Improved Text Modeling
Hao Tan, Chen-Tse Tsai, Yujie He, Mohit Bansal
Acronym Extraction with Hybrid Strategies
Siheng Li, Cheng Yang, Tian Liang, Xinyu Zhu, Chengze Yu, Yujiu Yang
Prompt-based Model for Acronym Disambiguation via Negative Sampling
Taiqiang Wu, Xingyu Bai, Yujiu Yang
Sequence Labeling for Citation Field Extractionfrom Cyrillic Script References
Igor Shapiro, Tarek Saier, Michael Färber
Segmenting Technical Drawing Figures in US Patents
Md Reshad Ul Hoque, Xin Wei, Muntabir Choudhury, Kehinde Ajayi, Martin Gryder, Jian Wu, Diane Oyen
A Novel Initial Reminder Framework for Acronym Extraction
Xiusheng Huang, Bin Li, Fei Xia, Yixuan Weng
A Framework for Automated Text Generation Benchmarking
Steven Layne, Sebastian Gehrmann, Franck Dernoncourt, Lidan Wang, Trung Bui, Walter Chang
Acronym Extraction and Acronym Disambiguation Shared Tasks at the Scientific Document Understanding Workshop 2022
Amir Pouran Ben Veyseh, Nicole Meister, Franck Dernoncourt, Thien Huu Nguyen

2022-06-15: submitted by Amir Pouran Ben Veyseh, metadata incl. bibliographic data published under Creative Commons CC0
2022-07-11: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|