CLEF-WN 2021
CLEF 2021 Working Notes

Table of Contents

• Preface
  Guglielmo Faggioli , Nicola Ferro , Alexis Joly , Maria Maistro , Florina Piroi
  

ARQMath: Answer Retrieval for Questions on Math

• Overview of ARQMath-2 (2021): Second CLEF Lab on Answer Retrieval for Questions on Math (Working Notes Version) 1 - 24
  Behrooz Mansouri , Richard Zanibbi , Douglas W. Oard , Anurag Agarwal
  
• XY-PHOC Symbol Location Embeddings for Math Formula Retrieval and Autocompletion 25 - 35
  Robin Avenoso , Behrooz Mansouri , Richard Zanibbi
  
• BERT-Based Embedding Model for Formula Retrieval 36 - 46
  Pankaj Dadure , Partha Pakray , Sivaji Bandyopadhyay
  
• DPRL Systems in the CLEF 2021 ARQMath Lab: Sentence-BERT for Answer Retrieval, Learning-to-Rank for Formula Retrieval 47 - 62
  Behrooz Mansouri , Douglas W. Oard , Richard Zanibbi
  
• Dowsing for Answers to Math Questions: Ongoing Viability of Traditional MathIR 63 - 81
  Yin Ki Ng , Dallas Fraser , Besat Kassaie , Frank Tompa
  
• Ensembling Math Information Retrieval Systems: MIRMU and MSM at ARQMath 2021 82 - 106
  Vít Novotný , Michal Štefánik , Dávid Lupták , Martin Geletka , Petr Zelina , Petr Sojka
  
• TU_DBS in the ARQMath Lab 2021, CLEF 107 - 124
  Anja Reusch , Maik Thiele , Wolfgang Lehner
  
• Ranked List Fusion and Re-ranking with Pre-trained Transformers for ARQMath Lab 125 - 132
  Shaurya Rohatgi , Jian Wu , C Lee Giles
  
• Approach Zero and Anserini at the CLEF-2021 ARQMath Track: Applying Substructure Search and BM25 on Operator Tree Path Tokens 133 - 156
  Wei Zhong , Xinyu Zhang , Ji Xin , Richard Zanibbi , Jimmy Lin
  

BioASQ: Large-scale biomedical semantic indexing and question answering

• Overview of BioASQ Tasks 9a, 9b and Synergy in CLEF2021 157 - 164
  Anastasios Nentidis , Georgios Katsimpras , Eirini Vandorou , Anastasia Krithara , Georgios Paliouras
  
• Overview of BioASQ 2021-MESINESP track. Evaluation of advance hierarchical classification techniques for scientific literature, patents and clinical trials. 165 - 187
  Luis Gasco , Anastasios Nentidis , Anastasia Krithara , Darryl Estrada-Zavala , Renato Toshiyuki Murasaki , Elena Primo-Peña , Cristina Bojo-Canales , Georgios Paliouras , Martin Krallinger
  
• BioASQ Synergy: A strong and simple baseline rooted in relevance feedback 188 - 195
  Tiago Almeida , Sérgio Matos
  
• Universal Passage Weighting Mecanism (UPWM) in BioASQ 9b 196 - 212
  Tiago Almeida , Sérgio Matos
  
• Large Biomedical Question Answering Models with ALBERT and ELECTRA 213 - 220
  Sultan Alrowili , Vijay Shanker
  
• Vicomtech at MESINESP2: BERT-based Multi-label Classification Models for Biomedical Text Indexing 221 - 230
  Aitor García-Pablos , Naiara Perez , Montse Cuadros
  
• MDS_UNCC Question Answering System for Biomedical Data with Preliminary Error Analysis 231 - 240
  Seethalakshmi Gopalakrishnan , Swathi Padithala , Hilmi Demirhan , Wlodek Zadrozny
  
• PIDNA at BioASQ MESINESP: Hybrid Semantic Indexing for Biomedical Articles in Spanish 241 - 246
  Yi Huang , Buse Giledereli , Abdullatif Koksal , Arzucan Ozgur , Elif Ozkirimli
  
• Transformer-based Language Models for Factoid Question Answering at BioASQ9b 247 - 257
  Urvashi Khanna , Diego Molla
  
• Post-processing BioBERT And Using Voting Methods for Biomedical Question Answering 258 - 273
  Margarida M. Campos , Francisco M. Couto
  
• Query-Focused Extractive Summarisation for Finding Ideal Answers to Biomedical and COVID-19 Questions 274 - 285
  Diego Molla , Urvashi Khanna , Dima Galat , Vincent Nguyen , Maciej Rybinski
  
• End-to-end Biomedical Question Answering via Bio-AnswerFinder and Discriminative Language Representation Models 286 - 301
  Ibrahim Burak Ozyurt
  
• A Neural Text Ranking Approach for Automatic MeSH Indexing 302 - 312
  Alastair Rae , James Mork , Dina Demner-Fushman
  
• COLE and LYS at BioASQ MESINESP Task: large scale multilabel text categorization with sparse and dense indices 313 - 323
  Francisco J. Ribadas-Pena , Shuyuan Cao , Elmurod Kuriyozov
  
• LASIGE-BioTM at MESINESP2: entity linking with semantic similarity and extreme multi-label classification on Spanish biomedical documents 324 - 334
  Pedro Ruas , Vitor D. T. Andrade , Francisco M. Couto
  
• NLM at BioASQ Synergy 2021: Deep Learning-based Methods for Biomedical Semantic Question Answering about COVID-19 335 - 350
  Mourad Sarrouti , Deepak Gupta , Asma Ben Abacha , Dina Demner-Fushman
  
• KU-DMIS at BioASQ 9: Data-centric and model-centric approaches for biomedical question answering 351 - 359
  Wonjin Yoon , Jaehyo Yoo , Sumin Seo , Mujeen Sung , Minbyul Jeong , Gangwoo Kim , Jaewoo Kang
  
• NCU-IISR/AS-GIS: Results of Various Pre-trained Biomedical Language Models and Linear Regression Model in BioASQ Task 9b Phase B 360 - 368
  Yu Zhang , Jen-Chieh Han , Richard Tzong-Han Tsai
  

CheckThat!: Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News

• Overview of the CLEF-2021 CheckThat! Lab Task 1 on Check-Worthiness Estimation in Tweets and Political Debates 369 - 392
  Shaden Shaar , Maram Hasanain , Bayan Hamdan , Zien Sheikh Ali , Fatima Haouari , Alex Nikolov , Mucahid Kutlu , Yavuz Selim Kartal , Firoj Alam , Giovanni Da San Martino , Alberto Barrón-Cedeño , Ruben Miguez , Javier Beltrán , Tamer Elsayed , Preslav Nakov
  
• Overview of the CLEF-2021 CheckThat! Lab Task 2 on Detecting Previously Fact-Checked Claims in Tweets and Political Debates 393 - 405
  Shaden Shaar , Fatima Haouari , Watheq Mansour , Maram Hasanain , Nikolay Babulkov , Firoj Alam , Giovanni Da San Martino , Tamer Elsayed , Preslav Nakov
  
• Overview of the CLEF-2021 CheckThat! Lab: Task 3 on Fake News Detection 406 - 423
  Gautam Kishore Shahi , Julia Maria Struß , Thomas Mandl
  
• QMUL-SDS at CheckThat! 2021: Enriching Pre-Trained Language Models for the Estimation of Check-Worthiness of Arabic Tweets 424 - 429
  Amani S. Abumansour , Arkaitz Zubiaga
  
• SCUoL at CheckThat! 2021: An AraBERT Model for Check-Worthiness of Arabic Tweets 430 - 434
  Saud Althabiti , Mohammad Alsalka , Eric Atwell
  
• M82B at CheckThat! 2021: Multiclass Fake News Detection Using BiLSTM 435 - 445
  Sohel Siddique Ashik , Abdur Rahman Apu , Nusrat Jahan Marjana , Md. Sanzidul Islam , Md. Arid Hassan
  
• CIC at CheckThat! 2021: Fake News detection Using Machine Learning And Data Augmentation 446 - 454
  Noman Ashraf , Sabur Butt , Grigori Sidorov , Alexander Gelbukh
  
• MUCIC at CheckThat! 2021: FaDo-Fake News Detection and Domain Identification using Transformers Ensembling 455 - 464
  Fazlourrahman Balouchzahi , Hosahalli Lakshmaiah Shashirekha , Grigori Sidorov
  
• UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims 465 - 475
  Ipek Baris Schlicht , Angel Felipe Magnossão de Paula , Paolo Rosso
  
• SU-NLP at CheckThat! 2021: Check-Worthiness of Turkish Tweets 476 - 483
  Buse Carik , Reyyan Yeniterzi
  
• Aschern at CLEF CheckThat! 2021: Lambda-Calculus of Fact-Checked Claims 484 - 493
  Anton Chernyavskiy , Dmitry Ilvovsky , Preslav Nakov
  
• UAICS at CheckThat! 2021: Fake news detection 494 - 507
  Ciprian Gabriel Cusmuliuc , Matei Alexandru Amarandei , Ioana Pelin , Vlad-Iulian Cociorva , Adrian Iftene
  
• University of Regensburg at CheckThat! 2021:Exploring Text Summarization for Fake News Detection 508 - 519
  Philipp Hartl , Udo Kruschwitz
  
• CIVIC-UPM at CheckThat! 2021: Integration of Transformers in Misinformation Detection and Topic Classification 520 - 530
  Álvaro Huertas-García , Javier Huertas-Tato , Alejandro Martín , David Camacho
  
• Classifier for fake news detection and Topical Domain of News Articles 531 - 536
  William Kana Tsoplefack
  
• Nkovachevich at CheckThat! 2021: BERT fine-tuning approach to fake news detection 537 - 544
  Ninko Kovachevich
  
• NLP&IR@UNED at CheckThat! 2021: Check-worthiness estimation and fake news detection using transformer models 545 - 557
  Juan R. Martinez-Rico , Juan Martinez-Romo , Lourdes Araujo
  
• DIPS at CheckThat! 2021: Verified Claim Retrieval 558 - 571
  Simona Mihaylova , Iva Borisova , Dzhovani Chemishanov , Preslav Hadzhitsanev , Momchil Hardalov , Preslav Nakov
  
• NLytics at CheckThat! 2021: Multi-class fake news detection of news articles and domain identification with RoBERTa - a baseline model 572 - 581
  Albert Pritzkau
  
• NLytics at CheckThat! 2021: Detecting Previously Fact-Checked Claims by Measuring Semantic Similarity 582 - 591
  Albert Pritzkau
  
• NLytics at CheckThat! 2021: Check-Worthiness Estimation as a Regression Problem on Transformers 592 - 602
  Albert Pritzkau
  
• NITK_NLP at CheckThat! 2021: Ensemble Transformer Model for Fake News Classification 603 - 611
  Hariharan RamakrishnaIyer LekshmiAmmal , Anand Kumar Madasamy
  
• Team Sigmoid at CheckThat!2021 Task 3a: Multiclass fake news detection with Machine Learning 612 - 618
  Abdullah Al Mamun Sardar , Shahalu Akter Salma , Md. Sanzidul Islam , Md. Arid Hasan , Touhid Bhuiyan
  
• Qword at CheckThat! 2021: An Extreme Gradient Boosting Approach for Multiclass Fake News Detection 619 - 627
  Rudra Sarker Utsha , Mumenunnessa Keya , Md. Arid Hasan , Md. Sanzidul Islam
  
• GPLSI team at CheckThat! 2021: Fine-tuning BETO and RoBERTa 628 - 638
  Robiert Sepúlveda-Torres , Estela Saquete
  
• BeaSku at CheckThat! 2021: Fine–Tuning Sentence BERT with Triplet Loss and Limited Data 639 - 647
  Beata Skuczyńska , Shaden Shaar , Jennifer Spenader , Preslav Nakov
  
• BlackOps at CheckThat! 2021: User Profiles Analyze of Intelligent Detection on Fake Tweets Notebook for PAN 648 - 658
  S. M. Sohan , Sharun Akter Khusbu , Md. Sanzidul Islam , Md. Arid Hasan
  
• Accenture at CheckThat! 2021: Interesting claim identification and ranking with contextually sensitive lexical training data augmentation 659 - 669
  Evan Williams , Paul Rodrigues , Sieu Tran
  
• TOBB ETU at CheckThat! 2021: Data Engineering for Detecting Check-Worthy Claims 670 - 680
  Muhammed Said Zengin , Yavuz Selim Kartal , Mucahid Kutlu
  
• Fight for 4230 at CheckThat! 2021: Domain-Specific Preprocessing and Pretrained Model for Ranking Claims by Check-Worthiness 681 - 692
  Xinrui Zhou , Bohuai Wu , Pascale Fung
  

ChEMU: Cheminformatics Elsevier Melbourne University lab

• Extended Overview of ChEMU 2021: Reaction Reference Resolution and Anaphora Resolution in Chemical Patents 693 - 709
  Yuan Li , Biaoyan Fang , Jiayuan He , Hiyori Yoshikawa , Saber A Akhondi , Christian Druckenbrodt , Camilo Thorne , Zubair Afzal , Zenan Zhai , Timothy Baldwin , Karin Verspoor
  
• A pipelined approach to Anaphora Resolution in Chemical Patents 710 - 719
  Ritam Dutt , Sopan Khosla , Carolyn Rose
  
• HUKB at ChEMU 2021 Task 2: Anaphora Resolution 720 - 731
  Kojiro Machi , Masaharu Yoshioka
  

eHealth: CLEFeHealth

• Overview of CLEF eHealth Task 1 - SpRadIE: A challenge on information extraction from Spanish Radiology Reports 732 - 750
  Viviana Cotik , Laura Alonso Alemany , Darío Filippo , Franco Luque , Roland Roller , Jorge Vivaldi , Ammer Ayach , Fernando Carranza , Lucas Defrancesca , Antonella Dellanzo , Macarena Fernández Urquiza
  
• Consumer Health Search at CLEF eHealth 2021 751 - 769
  Lorraine Goeuriot , Hanna Suominen , Gabriella Pasi , Elias Bassani , Nicola Brew-Sam , Gabriela Nicole González Sáez , Liadh Kelly , Philippe Mulhem , Sandaru Seneviratne , Rishabh Upadhyay , Marco Viviani , Chenchen Xu
  
• IMS-UNIPD @ CLEF eHealth Task 1: A Memory Based Reproducible Baseline 770 - 774
  Giorgio Maria Di Nunzio
  
• IMS-UNIPD @ CLEF eHealth Task 2: Reciprocal Ranking Fusion in CHS 775 - 779
  Giorgio Maria Di Nunzio , Federica Vezzani
  
• LSI_UNED at CLEF eHealth2021: Exploring the effects of transfer learning in negation detection and entity recognition in clinical texts 780 - 793
  Hermenegildo Fabregat , Andres Duque , Lourdes Araujo , Juan Martinez-Romo
  
• Pre-trained language models to extract information from radiological reports 794 - 803
  Pilar López-Úbeda , Manuel Carlos Díaz-Galiano , L. Alfonso Ureña-López , M. Teresa Martín-Valdivia
  
• Extracting information from radiology reports by Natural Language Processing and Deep Learning 804 - 817
  Miguel Ángel Martín-Caro García-Largo , Isabel Segura-Bedmar
  
• Comparing Transformer-based NER approaches for analysing textual medical diagnoses 818 - 833
  Marco Polignano , Marco de Gemmis , Giovanni Semeraro
  
• Information Extraction from Spanish Radiology Reports using multilingual BERT 834 - 845
  Oswaldo Solarte-Pabón , Orlando Montenegro , Alberto Blazquez-Herranz , Hadi Saputro , Alejandro Rodriguez-González , Ernestina Menasalvas
  
• A multi-BERT hybrid system for Named Entity Recognition in Spanish radiology reports 846 - 856
  Víctor Suárez-Paniagua , Hang Dong , Arlene Casey
  
• Learning to rank for Consumer Health Search 857 - 863
  Hua Yang , Xiaoming Liu , Binbin Zheng , Guan Yang
  

eRisk: Early Risk Prediction on the Internet

• Overview of eRisk at CLEF 2021: Early Risk Prediction on the Internet (Extended Overview) 864 - 887
  Javier Parapar , Patricia Martín-Rodilla , David E. Losada , Fabio Crestani
  
• Predicting Sign of Depression via Using Frozen Pre-trained Models and Random Forest Classifier 888 - 896
  Hassan Alhuzali , Tianlin Zhang , Sophia Ananiadou
  
• VADER meets BERT: sentiment analysis for early detection of signs of self-harm through social mining 897 - 907
  Lucas Barros , Alina Trifan , José Luis Oliveira
  
• UPV-Symanto at eRisk 2021: Mental Health Author Profiling for Early Risk Prediction on the Internet 908 - 927
  Angelo Basile , Mara Chinea-Rios , Ana-Sabina Uban , Thomas Müller , Luise Rössler , Seren Yenikent , Berta Chulví , Paolo Rosso , Marc Franco-Salvador
  
• Exploring the Performance of Baseline Text Mining Frameworks for Early Prediction of Self Harm Over Social Media 928 - 937
  Tanmay Basu , Georgios V Gkoutos
  
• Early Risk Detection of Pathological Gambling, Self-Harm and Depression Using BERT 938 - 949
  Ana-Maria Bucur , Adrian Cosma , Liviu P. Dinu
  
• NLP-UNED at eRisk 2021: self-harm early risk detection with TF-IDF and linguistic features 950 - 965
  Elena Campillo-Ageitos , Hermenegildo Fabregat , Lourdes Araujo , Juan Martinez-Romo
  
• uOttawa at eRisk 2021: Automatic Filling of the Beck's Depression Inventory Questionnaire using Deep Learning 966 - 980
  Diana Inkpen , Ruba Skaik , Prasadith Buddhitha , Dimo Angelov , Maxwell Thomas Fredenburgh
  
• CeDRI at eRisk 2021: A Naive Approach to Early Detection of Psychological Disorders in Social Media 981 - 991
  Rui Pedro Lopes
  
• UNSL at eRisk 2021: A Comparison of Three Early Alert Policies for Early Risk Detection 992 - 1021
  Juan Martín Loyola , Sergio Burdisso , Horacio Thompson , Leticia Cagnina , Marcelo Errecalde
  
• UniOR NLP at eRisk 2021: Assessing the Severity of Depression with Part of Speech and Syntactic Features 1022 - 1030
  Raffaele Manna , Johanna Monti
  
• Early Detection of Signs of Pathological Gambling, Self-Harm and Depression through Topic Extraction and Neural Networks 1031 - 1045
  Diego Maupomé , Maxime D. Armstrong , Fanny Rancourt , Thomas Soulas , Marie-Jean Meurs
  
• Transfer Learning for Automated Responses to the BDI Questionnaire 1046 - 1058
  Christoforos Spartalis , George Drosatos , Avi Arampatzis
  
• Towards transfer learning using BERT for early detection of self-harm of social media users 1059 - 1070
  Qamar Un Nisa , Rafi Muhammad
  
• A RoBERTa-based model on measuring the severity of the signs of depression 1071 - 1080
  Shih-Hung Wu , Zhao-Jun Qiu
  

ImageCLEF: Multimedia Retrieval Challenge in CLEF

• Overview of the VQA-Med Task at ImageCLEF 2021: Visual Question Answering and Generation in the Medical Domain 1081 - 1088
  Asma Ben Abacha , Mourad Sarrouti , Dina Demner-Fushman , Sadid A. Hasan , Henning Müller
  
• Overview of ImageCLEFtuberculosis 2021 - CT-based Tuberculosis Type Classification 1089 - 1100
  Serge Kozlovski , Vitali Liauchuk , Yashin Dicente Cid , Vassili Kovalev , Henning Müller
  
• Overview of the ImageCLEFmed 2021 Concept & Caption Prediction Task 1101 - 1112
  Obioma Pelka , Asma Ben Abacha , Alba Garcia Seco de Herrera , Janadhip Jacutprakart , Christoph M. Friedrich , Henning Müller
  
• Overview of ImageCLEFcoral 2021: Coral Reef Image Annotation of a 3D Environment 1113 - 1120
  Jon Chamberlain , Alba García Seco De Herrera , Antonio Campello , Adrian Clark , Thomas Oliver , Hassan Moustahfid
  
• Overview of the 2021 ImageCLEFdrawnUI Task: Detection and Recognition of Hand Drawn and Digital Website UIs 1121 - 1132
  Raul Berari , Andrei Tăuteanu , Dimitri Fichou , Paul Brie , Mihai Dogariu , Liviu-Daniel Ștefan , Mihai Gabriel Constantin , Bogdan Ionescu
  
• Classification of Tuberculosis Type on CT Scans of Lungs using a fusion of 2D and 3D Deep Convolutional Neural Networks 1133 - 1144
  Emad Aghajanzadeh , Behzad Shomali , Diba Aminshahidi , Navid Ghassemi
  
• Simple Neural Network based TB Classification 1145 - 1150
  Anirudh Anand , Karthik Raja Anandan , Bhuvana Jayaraman , Mirnalinee Thanga Nadar Thanga Thai
  
• ImageCLEF 2021: Deep categorizing tuberculosis cases using normalization and pseudo-color CT image 1151 - 1159
  Tetsuya Asakawa , Riku Tsuneda , Kazuki Shimizu , Takuyuki Komoda , Masaki Aono
  
• Attention-based CNN-GRU Model For Automatic Medical Images Captioning: ImageCLEF 2021 1160 - 1173
  Djamila-Romaissa Beddiar , Mourad Oussalah , Tapio Seppänen
  
• PUC Chile team at Caption Prediction: ResNet visual encoding and caption classification with Parametric ReLU 1174 - 1183
  Vicente Castro , Pablo Pino , Denis Parra , Hans Lobel
  
• AUEB NLP Group at ImageCLEFmed Caption Tasks 2021 1184 - 1200
  Foivos Charalampakos , Vasilis Karatzas , Vasiliki Kougia , John Pavlopoulos , Ion Androutsopoulos
  
• Chabbiimen at VQA-Med 2021: Visual Generation of Relevant Natural Language Questions from Radiology Images for Anomaly Detection 1201 - 1210
  Imen Chebbi
  
• TeamS at VQA-Med 2021: BBN-Orchestra for Long-tailed Medical Visual Question Answering 1211 - 1217
  Sedigheh Eslami , Gerard de Melo , Christoph Meinel
  
• SYSU-HCP at VQA-Med 2021: A Data-centric Model with Efficient Training Methodology for Medical Visual Question Answering 1218 - 1228
  Haifan Gong , Ricong Huang , Guanqi Chen , Guanbin Li
  
• A Convolutional Neural Networks based Coral Reef Annotation and Localization 1229 - 1238
  Rohit Gunti , Abebe Rorissa
  
• UI element detection from wireframe drawings of websites 1239 - 1252
  Prasang Gupta , Vishakha Bansal
  
• UAIC2021: Lung Analysis for Tuberculosis Classification 1253 - 1263
  Alexandra Hanganu , Cristian Simionescu , Lucia-Georgiana Coca , Adrian Iftene
  
• NLIP-Essex-ITESM at ImageCLEFcaption 2021 task : Deep Learning-based Information Retrieval and Multi-label Classification towards improving Medical Image Understanding 1264 - 1274
  Janadhip Jacutprakart , Francisco Parrilla Andrade , Rodolfo Cuan , Arely Aceves Compean , Giorgos Papanastasiou , Alba Garcia Seco de Herrera
  
• Lijie at ImageCLEFmed VQA-Med 2021: Attention Model-based Efficient Interaction between Multimodality 1275 - 1284
  Jie Li , Shengyan Liu
  
• Lijie at ImageCLEFmed Tuberculosis 2021: EfficientNet Simplified Tuberculosis Case Classification 1285 - 1294
  Jie Li , Li Yang , Yang Bai
  
• TAM at VQA-Med 2021: A Hybrid Model with Feature Extraction and Fusion for Medical Visual Question Answering 1295 - 1304
  Yong Li , Zhenguo Yang , Tianyong Hao
  
• Multi-Classification Study of the Tuberculosis with 3D CBAM-ResNet and EfficientNet 1305 - 1309
  Xing Lu , Eric Y Chang , Chun-Nan Hsu , Jiang Du , Amilcare Gentili
  
• Identifying tuberculosis type in CTs 1310 - 1316
  Cosmin Moisii , Radu Miron , Mihaela Breaban
  
• AEHRC CSIRO at ImageCLEFmed Caption 2021 1317 - 1328
  Aaron Nicolson , Jason Dowling , Bevan Koopman
  
• SSN MLRG at VQA-MED 2021: An Approach for VQA to Solve Abnormality Related Queries using Improved Datasets 1329 - 1335
  Noor Mohamed Sheerin Sitara , Srinivasan Kavitha
  
• PUC Chile team at TBT Task: Diagnosis of Tuberculosis Type using segmented CT scans 1336 - 1345
  José Miguel Quintana , Daniel Florea , Ria Deane , Denis Parra , Pablo Pino , Pablo Messina , Hans Löbel
  
• PUC Chile team at VQA-Med 2021: approaching VQA as a classification task via fine-tuning a pretrained CNN 1346 - 1351
  Ricardo Schilling , Pablo Messina , Denis Parra , Hans Löbel
  
• PUC Chile team at Concept Detection: K Nearest Neighbors with Perceptual Similarity 1352 - 1358
  Gregory Schuit , Vicente Castro , Pablo Pino , Denis Parra , Hans Lobel
  
• Automatic Coral Reef Annotation, Localization and Pixel-wise Parsing Using Mask R-CNN 1359 - 1364
  Lukáš Soukup
  
• Kdelab at ImageCLEF 2021: Medical Caption Prediction with Effective Data Pre-processing and Deep Learning 1365 - 1374
  Riku Tsuneda , Tetsuya Asakawa , Masaki Aono
  
• Improving web user interface element detection using Faster R-CNN 1375 - 1386
  Jiří Vyskočil , Lukáš Picek
  
• ImageSem Group at ImageCLEFmed Caption 2021 Task: Exploring the Clinical Significance of the Textual Descriptions Derived from Medical Images 1387 - 1393
  Xuwen Wang , Zhen Guo , Chunyuan Xu , Lianglong Sun , Jiao Li
  
• Pixelwise annotation of coral reef substrates 1394 - 1404
  Jessica Wright , Ioana-Lia Palosanu , Louis Clift , Alba García Seco de Herrera , Jon Chamberlain
  
• Yunnan University at VQA-Med 2021: Pretrained BioBERT for Medical Domain Visual Question Answering 1405 - 1411
  Qian Xiao , Xiaobing Zhou , Ya Xiao , Kun Zhao
  
• ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scans 1412 - 1421
  Hasib Zunair , Aimon Rahman , Nabeel Mohammed
  

LifeCLEF: Multimedia Life Species Identification

• Overview of PlantCLEF 2021: cross-domain plant identification 1422 - 1436
  Hervé Goëau , Pierre Bonnet , Alexis Joly
  
• Overview of BirdCLEF 2021: Bird call identification in soundscape recordings 1437 - 1450
  Stefan Kahl , Tom Denton , Holger Klinck , Hervé Glotin , Hervé Goëau , Willem-Pier Vellinga , Robert Planqué , Alexis Joly
  
• Overview of GeoLifeCLEF 2021: Predicting species distribution from 2 million remote sensing images 1451 - 1462
  Titouan Lorieul , Elijah Cole , Benjamin Deneu , Maximilien Servajean , Pierre Bonnet , Alexis Joly
  
• Overview of SnakeCLEF 2021: Automatic Snake Species Identification with Country-Level Focus 1463 - 1476
  Lukáš Picek , Andrew Durso , Isabelle Bolon , Rafael Ruiz de Castaneda
  
• EfficientNets and Vision Transformers for Snake Species Identification Using Image and Location Information 1477 - 1498
  Louise Bloch , Christoph M. Friedrich
  
• Incorporation of object detection models and location data into snake species classification 1499 - 1511
  Regő Borsodi , Dávid Papp
  
• A Deep Learning Method for Visual Recognition of Snake Species 1512 - 1525
  Rail Chamidullin , Milan Šulc , Jiří Matas , Lukáš Picek
  
• Improved Herbarium-Field Triplet Network for Cross-Domain Plant Identification: NEUON Submission to LifeCLEF 2021 Plant 1526 - 1539
  Sophia Chulif , Yang Loong Chang
  
• UAIC-AI at SnakeCLEF 2021: Impact of convolutions in snake species recognition 1540 - 1546
  Lucia Georgiana Coca , Alexia Theodora Popa , Razvan Contantin Croitoru , Luciana Paraschiva Bejan , Adrian Iftene
  
• Weakly-Supervised Classification and Detection of Bird Sounds in the Wild. A BirdCLEF 2021 Solution 1547 - 1558
  Marcos V. Conde , Kumar Shubham , Prateek Agnihotri , Nitin D. Movva , Szilard Bessenyei
  
• Bird-Species Audio Identification, Ensembling 1D + 2D Signals 1559 - 1570
  Gyanendra Das , Saksham Aggarwal
  
• Snake Species Classification using Transfer Learning Technique 1571 - 1578
  Karthik Desingu , Mirunalini Palaniappan , Jitesh Kumar
  
• Recognizing bird species in diverse soundscapes under weak supervision 1579 - 1586
  Christof Henkel , Pascal Pfeiffer , Philipp Singer
  
• Automatic Snake Classification using Deep Learning Algorithm 1587 - 1596
  Lekshmi Kalinathan , Prabavathy Balasundaram , Pradeep Ganesh , Sandeep Sekhar Bathala , Rahul Kumar Mukesh
  
• Birdcall Identification Using CNN and Gradient Boosting Decision Trees with Weak and Noisy Supervision 1597 - 1608
  Naoki Murakami , Hajime Tanaka , Masataka Nishimori
  
• STFT Transformers for Bird Song Recognition 1609 - 1616
  Jean-Francois Puget
  
• TUC Media Computing at BIRDCLEF 2021: Noise augmentation strategies in bird sound classification in combination with DenseNets and ResNets 1617 - 1626
  Arunodhayan Sampathkumar , Danny Kowerko
  
• Learning to Monitor Birdcalls From Weakly-Labeled Focused Recordings 1627 - 1638
  Jan Schlüter
  
• Contrastive Representation Learning for Natural World Imagery: Habitat prediction for 30,000 species 1639 - 1648
  Sachith Seneviratne
  
• BirdCLEF 2021: building a birdcall segmentation model based on weak labels 1649 - 1658
  Maxim Shugaev , Naoya Tanahashi , Philip Dhingra , Urvish Patel
  
• Weighted Pseudo Labeling Refinement for Plant Identification 1659 - 1667
  Youshan Zhang , Brian Davison
  

LiLAS: Living Labs for Academic Search

• Overview of LiLAS 2021 – Living Labs for Academic Search (Extended Overview) 1668 - 1699
  Philipp Schaer , Timo Breuer , Leyla Jael Castro , Benjamin Wolff , Johann Schaible , Narges Tavakolpoursaleh
  
• TEKMA at CLEF-2021: BM-25 based rankings for scientific publication retrieval and data set recommendation 1700 - 1711
  Jüri Keller , Leon Paul Mondrian Munz
  
• PyTerrier-based Research Data Recommendations for Scientific Articles in the Social Sciences 1712 - 1722
  Narges Tavakolpoursaleh , Johann Schaible
  
• Ad-hoc Retrieval of scientific Documents on the LIVIVO Search Portal 1723 - 1742
  Anh Huy Matthias Tran , Andreas Kruff , Joshua Thos , Constantin Krah , Michelle Reiners , Fabian Ax , Saskia Brech , Sascha Gharib , Verena Pawlas
  

PAN: Lab on Digital Text Forensics and Stylometry

• Overview of the Cross-Domain Authorship Verification Task at PAN 2021 1743 - 1759
  Mike Kestemont , Enrique Manjavacas , Ilia Markov , Janek Bevendorff , Matti Wiegmann , Efstathios Stamatatos , Benno Stein , Martin Potthast
  
• Overview of the Style Change Detection Task at PAN 2021 1760 - 1771
  Eva Zangerle , Maximilian Mayerl , Martin Potthast , Benno Stein
  
• Profiling Hate Speech Spreaders on Twitter Task at PAN 2021 1772 - 1789
  Francisco Rangel , Gretel Liz De La Peña Sarracén , Berta Chulvi , Elisabetta Fersini , Paolo Rosso
  
• Profiling Hate Spreaders using word N-grams 1790 - 1795
  Jorge Alcañiz , José Andrés
  
• Profiling Hate Speech Spreaders by Classifying Micro Texts Using BERT Model 1796 - 1800
  Esam Alzahrani , Leon Jololian
  
• Profiling Hate Speech Spreaders on Twitter 1801 - 1807
  Àngel Andújar Carracedo , Raquel Jiménez Mondéjar
  
• Identify Hate Speech Spreaders on Twitter using Transformer Embeddings Features and AutoML Classifiers 1808 - 1812
  Talha Anwar
  
• Profiling Haters on Twitter using Statistical and Contextualized Embeddings 1813 - 1821
  Hamed Babaei Giglou , Taher Rahgooy , Jafar Razmara , Mostafa Rahgouy , Zahra Rahgooy
  
• Profiling Spreaders of Hate Speech with N-grams and RoBERTa 1822 - 1828
  Christopher Bagdon
  
• HSSD: Hate Speech Spreader Detection using N-grams and Voting Classifier 1829 - 1836
  Fazlourrahman Balouchzahi , Shashirekha Hosahalli Lakshmaiah , Grigori Sidorov
  
• Unified and Multilingual Author Profiling for Detecting Haters 1837 - 1845
  Ipek Baris Schlicht , Angel Felipe Magnossão de Paula
  
• O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification 1846 - 1857
  Benedikt Bönninghoff , Robert Nickel , Dorothea Kolossa
  
• INFOTEC-LaBD at PAN@CLEF21: Profiling Hate Speech Spreaders on Twitter through Emotion-based Representations 1858 - 1870
  Hiram Cabrera , Sabino Miranda , Eric Tellez
  
• Exploiting Contextualized Word Representations to Profile Haters on Twitter 1871 - 1882
  Tanise Ceron , Camilla Casula
  
• Use of Lexical and Psycho-Emotional Information to Detect Hate Speech Spreaders on Twitter - Notebook for PAN at CLEF 2021 1883 - 1891
  Riccardo Cervero
  
• Profiling Hate Speech Spreaders on Twitter 1892 - 1898
  Kumar Gourav Das , Buddhadeb Garai , Srijan Das , Braja Gopal Patra
  
• Style Change Detection on Real-World Data using an LSTM-powered Attribution Algorithm 1899 - 1909
  Robert Deibel , Denise Loefflad
  
• Detection of Hate Speech Spreaders with BERT 1910 - 1919
  David Dukić , Ana Sović Kržić
  
• Graph-based Siamese Network for Authorship Verification 1920 - 1930
  Daniel Embarcadero-Ruiz , Helena Gómez-Adorno , Ivan Reyes-Hernández , Alexis García , Alberto Embarcadero-Ruiz
  
• Profiling Hate Speech Spreaders using Characters andWords N-grams 1931 - 1936
  Daniel Espinosa , Grigori Sidorov
  
• Hate speech spreader detection using contextualized word embeddings 1937 - 1944
  Evgeny Finogeev , Mariam Kaprielova , Artem Chashchin , Kirill Grashchenkov , George Gorbachev , Oleg Bakhteev
  
• Author classification as pre-training for pairwise authorship verification 1945 - 1952
  Romain Futrzynski
  
• Profiling Hate Speech Spreaders on Twitter using stylistic features and word embeddings 1953 - 1962
  Lucía Gómez Zaragozá , Sara Hinojosa Pinto
  
• Profiling Hate Speech Spreaders on Twitter: Transformers and mixed pooling 1963 - 1975
  Álvaro Huertas-García , Javier Huertas-Tato , Alejandro Martín , David Camacho
  
• Effective Detection of Hate Speech Spreaders on Twitter 1976 - 1986
  Julian Höllig , Yeong Su Lee , Nina Seemann , Michaela Geierhos
  
• UniNE at PAN-CLEF 2021 1987 - 1994
  Catherine Ikae
  
• UniNE at PAN-CLEF 2021: Authorship Verification 1995 - 2003
  Catherine Ikae
  
• Early Detection of Online Hate Speech Spreaders with Learned User Representations 2004 - 2010
  Darius Irani , Avyakta Wrat , Silvio Amir
  
• Profiling Hate Speech Spreaders on Twitter 2011 - 2024
  Rakshita Jain , Devanshi Goel , Prashant Sahu , Abhinav Kumar , Jyoti Prakash Singh
  
• Using N-grams and Statistical Features to Identify Hate Speech Spreaders on Twitter 2025 - 2034
  Eszter Katona , Jakab Buda , Flora Bolonyai
  
• Deep Modeling of Latent Representations for Twitter Profiles on Hate Speech Spreaders Identification. Notebook for PAN at CLEF 2021 2035 - 2046
  Roberto Labadie , Daniel Castro-Castro , Reynier Ortega Bueno
  
• HaMor at the Profiling Hate Speech Spreaders on Twitter 2047 - 2055
  Mirko Lai , Marco Antonio Stranisci , Cristina Bosco , Rossana Damiano , Viviana Patti
  
• Authorship Verification based on Lucene architecture 2056 - 2059
  Zhihao Liao , Yong Han , Leilei Kong , Zhuopeng Hong , Zijian Li , Guiyuan Liang , Zhenwei Mo , Zhixian Li , Zhongyuan Han
  
• Hate Speech Detection on Twitter 2060 - 2063
  Carolina Martin del Campo Rodriguez , Grigori Sidorov , Ildar Batyrshin
  
• Authorship Verification with neural networks via stylometric feature concatenation 2064 - 2068
  Antonio Menta , Ana Garcia-Serrano
  
• Dual Neural Network Classification Based on BERT Feature Extraction for Authorship Verification 2069 - 2072
  Xiaogang Miao , Haoliang Qi , Zhijie Zhang , Guiyuan Cao , Ruilan Lin , Wenbin Lin
  
• Style change detection using Siamese neural networks 2073 - 2082
  Sukanya Nath
  
• University of Regensburg @ PAN: Profiling Hate Speech Spreaders on Twitter 2083 - 2089
  Kwabena Odame Akomeah , Udo Kruschwitz , Bernd Ludwig
  
• Local Classification with Recurrent Neural Network for Profiling Hate Speech Spreaders on Twitter. Notebook for PAN at CLEF 2021 2090 - 2102
  Pablo Pallarés , Carlos Herrero
  
• Encoding Text Information By Pre-trained Model For Authorship Verification 2103 - 2107
  Zeyang Peng , Leilei Kong , Zhijie Zhang , Zhongyuan Han , Xu Sun
  
• Feature Similarity-based Regression Models for Authorship Verification 2108 - 2117
  Marina Pinzhakova , Tom Yagel , Jakov Rabinovits
  
• Phonetic Detection for Hate Speech Spreaders on Twitter 2118 - 2125
  Edwin Puertas , Juan Carlos Martinez-Santos
  
• Detection of hate speech spreaders using convolutional neural networks 2126 - 2136
  Marco Siino , Elisa Di Nuovo , Ilenia Tinnirello , Marco La Cascia
  
• Writing Style Change Detection on Multi-Author Documents 2137 - 2145
  Rhia Singh , Janith Weerasinghe , Rachel Greenstadt
  
• Multi-label Style Change Detection by Solving a Binary Classification Problem 2146 - 2157
  Eivind Strøm
  
• Multi-level stacked ensemble with sparse and dense features for hate speech detection on Twitter 2158 - 2168
  Darko Tosev , Sonja Gievska
  
• Siamese Bert for Authorship Verification 2169 - 2177
  Jacob Tyo , Bhuwan Dhingra , Zachary Lipton
  
• Detecting Hate Speech Spreaders on Twitter using LSTM and BERT in English and Spanish 2178 - 2185
  Moshe Uzan , Yaakov Hacohen-Kerner
  
• Profiling Hate Speech Spreaders on Twitter: Exploiting Textual Analysis of Tweets and Combination of Textual Representations 2186 - 2192
  Claudio Moisés Valiense de Andrade , Marcos André Gonçalves
  
• Profiling Hate Speech Spreaders on Twitter: SVM vs. Bi-LSTM 2193 - 2200
  Inna Vogel , Meghana Meghana
  
• Feature Vector Difference based Authorship Verification for Open-World Settings 2201 - 2207
  Janith Weerasinghe , Rhia Singh , Rachel Greenstadt
  
• Style Change Detection Based On Writing Style Similarity 2208 - 2211
  Zhijie Zhang , Zhongyuan Han , Leilei Kong , Xiaogang Miao , Zeyang Peng , Jieming Zeng , Haojie Cao , Jinxi Zhang , Ziwei Xiao , Xuemei Peng
  

SimpleText: (Re)Telling right scientific stories to non-specialists via text simplification

• Overview of SimpleText CLEF 2021 Workshop and Pilot Tasks 2212 - 2227
  Liana Ermakova , Patrice Bellot , Pavel Braslavski , Jaap Kamps , Josiane Mothe , Diana Nurbakova , Irina Ovchinnikova , Eric Sanjuan
  
• Overview of the SimpleText Workshop at INFORSID-2021: Scientific Text Simplification and Popularization 2228 - 2232
  Liana Ermakova , Josiane Mothe , Eric Sanjuan
  
• Multimodal science communication: from documentary research to infographic via mind mapping 2233 - 2236
  Sílvia Araújo , Radia Hannachi
  
• LIA@SimpleText2021: automatic query extraction from press outlets for mining related readable passages in scientific literature 2237 - 2241
  Malek Hajjem , Eric Sanjuan
  
• What Science-Related Topics Need to Be Popularized? A Comparative Study 2242 - 2255
  Irina Ovchinnikova , Diana Nurbakova , Liana Ermakova
  
• Importance of Data and Controllability in Neural Text Simplification 2256 - 2257
  Wei Xu
  

Touché: Argument Retrieval

• Overview of Touché 2021: Argument Retrieval 2258 - 2284
  Alexander Bondarenko , Lukas Gienapp , Maik Fröbe , Meriem Beloucif , Yamen Ajjour , Alexander Panchenko , Chris Biemann , Benno Stein , Henning Wachsmuth , Martin Potthast , Matthias Hagen
  
• Exploring Argument Retrieval for Controversial Questions Using Retrieve and Re-rank Pipelines 2285 - 2291
  Raunak Agarwal , Andrei Koniaev , Robin Schaefer
  
• Learning to Rank Arguments with Feature Selection 2292 - 2301
  Christopher Akiki , Maik Fröbe , Matthias Hagen , Martin Potthast
  
• Development of an IR System for Argument Search 2302 - 2318
  Marco Alecci , Tommaso Baldo , Luca Martinelli , Elia Ziroldo
  
• DistilBERT-based Argumentation Retrieval for Answering Comparative Questions 2319 - 2330
  Alaa Alhamzeh , Mohamed Bouhaouel , Elöd Egyed-Zsigmond , Jelena Mitrović
  
• Document retrieval task on controversial topic with Re-Ranking approach 2331 - 2353
  Andrea Cassetta , Alberto Piva , Enrico Vicentini
  
• Retrieving Comparative Arguments using Ensemble Methods and BERT 2354 - 2365
  Viktoriia Chekalina , Alexander Panchenko
  
• Quality-aware Argument Retrieval with Topical Clustering 2366 - 2373
  Lukas Gienapp
  
• Exploring BERT Synonyms and Quality Prediction for Argument Retrieval 2374 - 2388
  Tommaso Green , Luca Moroldo , Alberto Valente
  
• Touché Task 2: Comparative Argument Retrieval A document-based search engine for answering comparative questions 2389 - 2402
  Daniel Helmrich , Denis Streitmatter , Fionn Fuchs , Maximilian Heykeroth
  
• Argument Retrieval for Comparative Questions based on independent features 2403 - 2416
  Thi Kim Hanh Luu , Jan-Niklas Weder
  
• Exploring Document Expansion for Argument Retrieval 2417 - 2422
  Alina Mailach , Denise Arnold , Stefan Eysoldt , Simon Kleine
  
• A Search Engine System for Touché Argument Retrieval task to answer Controversial Questions 2423 - 2440
  Edoardo Raimondi , Marco Alessio , Nicola Levorato
  
• Team Skeletor at Touché 2021: Argument Retrieval and Visualization for Controversial Questions 2441 - 2454
  Kevin Ros , Carl Edwards , Heng Ji , Chengxiang Zhai
  
• Thor at Touché 2021: Argument Retrieval for Comparative Questions 2455 - 2462
  Ekaterina Shirshakova , Ahmad Wattar