CLEF-WN 2023
CLEF 2023 Working Notes

Table of Contents

• Preface I-X
  Summary: This volume contains the 265 working notes that were peer-reviewed and accepted for publication at CLEF 2023. Out of these, 33 are overviews of the labs and tasks, while 232 are the participants' working notes.

Large-scale biomedical semantic indexing and question answering (BioASQ)

• Overview of MedProcNER Task on Medical Procedure Detection and Entity Linking at BioASQ 2023 1-18
  Salvador Lima-López, Eulália Farré-Maduell, Luis Gascó, Anastasios Nentidis, Anastasia Krithara, Georgios Katsimpras, Georgios Paliouras, Martin Krallinger
• Overview of BioASQ Tasks 11b and Synergy11 in CLEF2023 19-26
  Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara, Georgios Paliouras
• Improving Biomedical Question Answering with Sentence-based Ranking at BioASQ-11b 27-36
  Anna Aksenova, Tsvetan Asamov, Petar Ivanov, Svetla Boytcheva
• BIT.UA at BioASQ 11B: Two-Stage IR with Synthetic Training and Zero-Shot Answer Generation 37-59
  Tiago Almeida, Richard A. A. Jonker, Roshan Poudel, Jorge M. Silva, Sérgio Matos
• BIT.UA at MedProcNer: Discovering Medical Procedures in Spanish Using Transformer Models with MCRF and Augmentation 60-72
  Tiago Almeida, Richard A. A. Jonker, Roshan Poudel, Jorge M. Silva, Sérgio Matos
• Is ChatGPT a Biomedical Expert? 73-90
  Samy Ateia, Udo Kruschwitz
• Coming a Long Way with Pre-Trained Transformers and String Matching Techniques: Clinical Procedure Mention Recognition and Normalization 91-101
  Mariia Chizhikova, Jaime Collado-Montañez, Manuel Carlos Díaz-Galiano, L. Alfonso Ureña-López, María Teresa Martín-Valdivia
• Enhancing Biomedical Text Summarization and Question-Answering: On the Utility of Domain-Specific Pre-Training 102-113
  Dima Galat, Marian-Andrei Rizoiu
• NCU-IISR: Prompt Engineering on GPT-4 to Stove Biological Problems in BioASQ 11b Phase B 114-121
  Chun-Yu Hsueh, Yu Zhang, Yu-Wei Lu, Jen-Chieh Han, Wilailack Meesawad, Richard Tzong-Han Tsai
• Leveraging Biomedical Ontologies for Clinical Procedures Recognition in Spanish at BioASQ MedProcNER 122-131
  Petar Ivanov, Anna Aksenova, Tsvetan Asamov, Svetla Boytcheva
• Exploring Approaches to Answer Biomedical Questions: From Pre-processing to GPT-4 132-144
  Hyunjae Kim, Hyeon Hwang, Chaeeun Lee, Minju Seo, Wonjin Yoon, Jaewoo Kang
• BioASQ 11B: Integrating Domain Specific Vocabulary to BERT-based Model for Biomedical Document Ranking. 145-151
  Maël Lesavourey, Gilles Hubert
• Semi-supervised training for biomedical question answering 152-158
  Dimitra Panou, Martin Reczko
• Biomedical Question Answering with Transformer Ensembles 159-167
  Raghav R, Jason Rauchwerk, Parth Rajwade, Tanay Gummadi, Eric Nyberg, Teruko Mitamura
• Deep Metric Learning for Effective Passage Retrieval in the BioASQ Challenge 168-177
  Andrés Rosso-Mateus, León A. Muñoz-Serna, Manuel Montes-Y-Gómez, Fabio A. González
• Multi-stage Literature Retrieval System Trained by PubMed Search Logs for Biomedical Question Answering 178-189
  Ashley Shin, Qiao Jin, Zhiyong Lu
• Fusion @ BioASQ MedProcNER: Transformer-based Approach for Procedure Recognition and Linking in Spanish Clinical Text 190-205
  Sylvia Vassileva, Georgi Grazhdanski, Svetla Boytcheva, Ivan Koychev
• VICOMTECH at MedProcNER 2023: Transformers-based Sequence-labelling and Cross-encoding for Entity Detection and Normalisation in Spanish Clinical Texts 206-218
  Elena Zotova, Aitor García-Pablos, Montse Cuadros, German Rigau

Check-Worthiness, Subjectivity, Political Bias, Factuality, and Authority of News Articles and Their Sources (CheckThat!)

• Overview of the CLEF-2023 CheckThat! Lab Task 1 on Check-Worthiness in Multimodal and Multigenre Content 219-235
  Firoj Alam, Alberto Barrón-Cedeño, Gullal S. Cheema, Gautam Kishore Shahi, Sherzod Hakimov, Maram Hasanain, Chengkai Li, Rubén Míguez, Hamdy Mubarak, Wajdi Zaghouani, Preslav Nakov
• Overview of the CLEF-2023 CheckThat! Lab: Task 2 on Subjectivity Detection 236-249
  Andrea Galassi, Federico Ruggeri, Alberto Barrón-Cedeño, Firoj Alam, Tommaso Caselli, Mucahid Kutlu, Julia Maria Struß, Francesco Antici, Maram Hasanain, Juliane Köhler, Katerina Korre, Folkert Leistra, Arianna Muti, Melanie Siegel, Mehmet Deniz Türkmen, Michael Wiegand, Wajdi Zaghouani
• Overview of the CLEF-2023 CheckThat! Lab Task 3 on Political Bias of News Articles and News Media 250-259
  Giovanni Da San Martino, Firoj Alam, Maram Hasanain, Rabindra Nath Nandi, Dilshod Azizov, Preslav Nakov
• Overview of the CLEF-2023 CheckThat! Lab Task 4 on Factuality of Reporting of News Media 260-268
  Preslav Nakov, Firoj Alam, Giovanni Da San Martino, Maram Hasanain, Dilshod Azizov, Rabindra Nath Nandi, Panayotov Panayot
• Overview of the CLEF-2023 CheckThat! Lab Task 5 on Authority Finding in Twitter 269-278
  Fatima Haouari, Tamer Elsayed, Zien Sheikh Ali
• CSECU-DSG at CheckThat! 2023: Transformer-based Fusion Approach for Multimodal and Multigenre Check-Worthiness 279-288
  Abdul Aziz, Md. Akram Hossain, Abu Nowshed Chy
• Frank at CheckThat! 2023: Detecting the Political Bias of News Articles and News Media 289-305
  Dilshod Azizov, Preslav Nakov, Shangsong Liang
• DWReCO at CheckThat! 2023: Enhancing Subjectivity Detection through Style-based Data Sampling 306-317
  Ipek Baris Schlicht, Lynn Khellaf, Defne Altiok
• NN at CheckThat! 2023: Subjectivity in News Articles Classification with Transformer Based Models 318-328
  Krishno Dey, Prerona Tarannum, Md. Arid Hasan, Sheak Rashed Haider Noori
• Fraunhofer SIT at CheckThat! 2023: Can LLMs Be Used for Data Augmentation & Few-Shot Classification? Detecting Subjectivity in Text Using ChatGPT 329-336
  Raphael Antonius Frick
• Fraunhofer SIT at CheckThat! 2023: Enhancing the Detection of Multimodal and Multigenre Check-Worthiness Using Optical Character Recognition and Model Souping 337-350
  Raphael Antonius Frick, Inna Vogel, Jeong-Eun Choi
• Thesis Titan at CheckThat! 2023: Language-Specific Fine-tuning of mDeBERTaV3 for Subjectivity Detection 351-359
  Folkert Atze Leistra, Tommaso Caselli
• CUCPLUS at CheckThat! 2023: Text Combination and Regularized Adversarial Training for News Media Factuality Evaluation 360-371
  Chenxin Li, Ruijin Xue, Chichen Lin, Weijian Fan, Xiao Han
• NLPIR-UNED at CheckThat! 2023: Ensemble of Classifiers for Check-Worthiness Estimation 372-382
  Juan R. Martinez-Rico, Lourdes Araujo, Juan Martinez-Romo
• DSHacker at CheckThat! 2023: Check-Worthiness in Multigenre and Multilingual Content With GPT-3.5 Data Augmentation 383-393
  Arkadiusz Modzelewski, Witold Sosnowski, Adam Wierzbicki
• TeamX at CheckThat! 2023: Multilingual and Multimodal Approach for Check-Worthines Detection 394-403
  Rabindra Nath Nandi, Firoj Alam
• Gpachov at CheckThat! 2023: A Diverse Multi-approach Ensemble for Subjectivity Detection in News Articles 404-412
  Georgi Pachov, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov
• ES-VRAI at CheckThat! 2023: Leveraging Bio and Lists Information for Enhanced Rumor Verification in Twitter 413-422
  Hamza Tarik Sadouk, Faouzi Sebbak, Hussem Eddine Zekiri
• ES-VRAI at CheckThat! 2023: Enhancing Model Performance for Subjectivity Detection through Multilingual Data Aggregation 423-429
  Hamza Tarik Sadouk, Faouzi Sebbak, Hussem Eddine Zekiri
• ES-VRAI at CheckThat! 2023: Analyzing Checkworthiness in Multimodal and Multigenre Contents through Fusion and Sampling Approaches 430-444
  Hamza Tarik Sadouk, Faouzi Sebbak, Hussem Eddine Zekiri
• FakeDTML at CheckThat! 2023: Identifying Check-Worthiness of Tweets and Debate Snippets 445-452
  Abdullah Al Mamun Sardar, Md. Ziaul Karim, Krishno Dey, Md. Arid Hasan
• OpenFact at CheckThat! 2023: Head-to-Head GPT vs. BERT - A Comparative Study of Transformers Language Models for the Detection of Check-worthy Claims 453-472
  Marcin Sawinski, Krzysztof Wecel, Ewelina Ksiezniak, Milena Strózyna, Wlodzimierz Lewoniewski, Piotr Stolarski, Witold Abramowicz
• TUDublin at CheckThat! 2023: ChatGPT for Data Augmentation 473-481
  Elena Shushkevich, John Cardiff
• Z-Index at CheckThat! 2023: Unimodal and Multimodal Check-worthiness Classification 482-493
  Prerona Tarannum, Md. Arid Hasan, Firoj Alam, Sheak Rashed Haider Noori
• Accenture at CheckThat! 2023: Learning to Detect Factuality Levels of News Sources 494-499
  Sieu Tran, Paul Rodrigues, Benjamin Strauss, Evan M. Williams
• Accenture at CheckThat! 2023: Learning to Detect Political Bias of News Articles and Sources 500-506
  Sieu Tran, Paul Rodrigues, Benjamin Strauss, Evan M. Williams
• Accenture at CheckThat! 2023: Impacts of Back-translation on Subjectivity Detection 507-517
  Sieu Tran, Paul Rodrigues, Benjamin Strauss, Evan M. Williams
• Accenture at CheckThat! 2023: Identifying Claims with Societal Impact using NLP Data Augmentation 518-525
  Sieu Tran, Paul Rodrigues, Benjamin Strauss, Evan M. Williams
• TOBB ETU at CheckThat! 2023: Utilizing ChatGPT to Detect Subjective Statements and Political Bias 526-533
  Mehmet Deniz Türkmen, Gökalp Cosgun, Mucahid Kutlu
• ZHAW-CAI at CheckThat! 2023: Ensembling using Kernel Averaging 534-545
  Pius von Däniken, Jan Deriu, Mark Cieliebak

Document Information Localization and Extraction (DocILE)

• Extended Overview of DocILE 2023: Document Information Localization and Extraction 546-571
  Štepán Šimsa, Michal Uricár, Milan Šulc, Yash Patel, Ahmed Hamdi, Matej Kocián, Matyáš Skalický, Jirí Matas, Antoine Doucet, Mickaël Coustaty, Dimosthenis Karatzas
• RoBERTa Ensemble Technique for Document Information Localization and Extraction 572-582
  Bao Gia Tran, Duy-Ngo Minh Bao, Khanh Gia Bui, Huy Viet Duong, Dang Hai Nguyen, Hieu Minh Nguyen
• Object Detection Pipeline Using YOLOv8 for Document Information Extraction 583-597
  Jakub Straka, Ivan Gruber
• USTC-iFLYTEK at DocILE: A Multi-modal Approach Using Domain-specific GraphDoc 598-610
  Yan Wang, Jun Du, Jiefeng Ma, Pengfei Hu, Zhenrong Zhang, Jianshu Zhang

Early Risk Prediction on the Internet (eRisk)

• Overview of eRisk at CLEF 2023: Early Risk Prediction on the Internet (Extended Overview) 611-638
  Javier Parapar, Patricia Martin-Rodilla, David E. Losada, Fabio Crestani
• NailP at eRisk 2023: Search for Symptoms of Depression 639-661
  Eduardo Bezerra, Leonardo dos Santos, Rodolpho Nascimento, Rui Pedro Lopes, Gustavo Guedes
• Utilizing ChatGPT Generated Data to Retrieve Depression Symptoms from Social Media 662-671
  Ana-Maria Bucur
• NLP-UNED-2 at eRisk 2023: Detecting Pathological Gambling in Social Media through Dataset Relabeling and Neural Networks 672-683
  Hermenegildo Fabregat, Andres Duque, Lourdes Araujo, Juan Martinez-Romo
• Transformer-based Topic Modeling to Measure the Severity of Eating Disorder Symptoms 684-692
  Diana-Nicoleta Grigore, Ioana Pintilie
• Representation Exploration and Deep Learning Applied to the Early Detection of Pathological Gambling Risks 693-705
  Xabier Larrayoz, Nuria Lebeña, Arantza Casillas, Alicia Pérez
• OBSER-MENH at eRisk 2023: Deep Learning-Based Approaches for Symptom Detection in Depression and Early Identification of Pathological Gambling Indicators 706-717
  Juan Martinez-Romo, Lourdes Araujo, Xabier Larrayoz, Maite Oronoz, Alicia Pérez
• Lightweight Methods for Early Risk Detection 718-726
  Diego Maupomé, Thomas Soulas, Fanny Rancourt, Ghyslain Cantin-Savoie, Grégoire Winterstein, Sébastien Mosser, Marie-Jean Meurs
• BFH-AMI at eRisk@CLEF 2023 727-735
  Ghofrane Merhbene, Alexandre R. Puttick, Mascha Kurpicz-Briki
• ELiRF-UPV at eRisk 2023: Early detection of pathological gambling using SVM 736-742
  Antonio Molina, Xinhui Huang, Lluís-F. Hurtado, Ferran Pla
• SINAI at eRisk@CLEF 2023: Approaching Early Detection of Gambling with Natural Language Processing 743-751
  Alba María Mármol-Romero, Flor Miriam Plaza-del-Arco, Arturo Montejo-Ráez
• UMUTeam at eRisk@CLEF 2023 Shared Task: Transformer Models for Early Detection of Pathological Gambling, Depression, and Eating Disorder 752-762
  Ronghao Pan, José Antonio García Díaz, Rafael Valencia-García
• Exploring Depression Symptoms through Similarity Methods in Social Media Posts 763-772
  Naveen Recharla, Prasanthi Bolimera, Yash Gupta, Anand Kumar Madasamy
• MASON-NLP at eRisk 2023: Deep Learning-Based Detection of Depression Symptoms from Social Media Texts 773-781
  Fardin Ahsan Sakib, Ahnaf Atef Choudhury, Ozlem Uzuner
• A Natural Language Processing Based Risk Prediction Framework for Pathological Gambling 782-790
  Abu Talha, Tanmay Basu
• Strategies to Harness the Transformers’ Potential: UNSL at eRisk 2023 791-804
  Horacio Thompson, Leticia Cagnina, Marcelo Errecalde
• uOttawa at eRisk 2023: Search for Symptoms of Depression 805-812
  Yuxi Wang, Diana Inkpen

sEXism Identification in Social neTworks (EXIST)

• Overview of EXIST 2023 – Learning with Disagreement for Sexism Identification and Characterization (Extended Overview) 813-854
  Laura Plaza, Jorge Carrillo-De-Albornoz, Roser Morante, Enrique Amigó, Julio Gonzalo, Damiano Spina, Paolo Rosso
• Multilingual Sexism Identification Using Contrastive Learning 855-861
  Jason Angel, Segun Taofeek Aroyehun, Alexander Gelbukh
• Tlatlamiztli: Fine-Tuned RoBERTuito for Sexism Detection 862-868
  Hardik Asnani, Andrew Davis, Aaryana Rajanala, Sandra Kübler
• IU-NLP-JeDi: Investigating Sexism Detection in English and Spanish 869-877
  Matthew Buzzell, Jeremy Dickinson, Natasha Singh, Sandra Kübler
• AIT_FHSTP at EXIST 2023 Benchmark: Sexism Detection by Transfer Learning, Sentiment and Toxicity Embeddings and Hand-Crafted Features 878-890
  Jaqueline Böck, Mina Schütz, Daria Liakhovets, Nathanya Queby Satriani, Andreas Babic, Djordje Slijepcevic, Matthias Zeppelzauer, Alexander Schindler
• Sexism Identification In Social Networks 891-900
  Atul Chaudhary, Ritesh Kumar
• I2C-UHU at CLEF-2023 EXIST task: Leveraging Ensembling Language Models to Detect Multilingual Sexism in Social Media 901-907
  Pablo Cordón, Jacinto Mata, Victoria Pachón, Juan Luis Domínguez
• When Multiple Perspectives and an Optimization Process Lead to Better Performance, an Automatic Sexism Identification on Social Media With Pretrained Transformers in a Soft Label Context 908-918
  Johan Erbani, Elöd Egyed-Zsigmond, Diana Nurbakova, Pierre-Edouard Portier
• CLassifiers at EXIST 2023: Detecting Sexism in Spanish and English Tweets With XLM-T 919-926
  Berna Ilke Ersoy, Gian Radler, Sofia Carpentieri
• IU-Percival: Linear Models for Sexism Detection 927-936
  Elizabeth Gabel, Holly Redman, Daniel Swanson, Sandra Kübler
• UMUTeam at EXIST 2023: Sexism identification and categorisation fine-tuning Multilingual Large Language Models 937-949
  José Antonio García-Díaz, Ronghao Pan, Rafael Valencia-García
• IUEXIST: Multilingual Pre-trained Language Models for Sexism Detection on Twitter in EXIST2023 950-958
  Yash A. Hatekar, Muhammad S. Abdo, Snigdha Khanna, Sandra Kübler
• Detection of Sexism on Social Media with Multiple Simple Transformers 959-966
  Chirayu Jhakal, Khushi Singal, Manan Suri, Divya Chaudhary, Bijendra Kumar, Ian Gorton
• ROH_NEIL@EXIST2023: Detecting Sexism in Tweets using Multilingual Language Models 967-984
  Rohit Koonireddy, Niloofar Adel
• AI-UPV at EXIST 2023 – Sexism Characterization Using Large Language Models Under The Learning with Disagreement Regime 985-999
  Angel Felipe Magnossão de Paula, Giulia Rizzi, Elisabetta Fersini, Damiano Spina
• Towards Robust Online Sexism Detection: A Multi-Model Approach with BERT, XLM-RoBERTa, and DistilBERT for EXIST 2023 Tasks 1000-1011
  Hadi Mohammadi, Anastasia Giachanou, Ayoub Bagheri
• Enriching Hate-Tuned Transformer-Based Embeddings with Emotions for the Categorization of Sexism 1012-1023
  Arianna Muti, Eleonora Mancini
• Combining Transformer Based Language Models with Socio-demographic Information for Improving Sexism Detection in Social Media 1024-1036
  Jacobo Pedrosa-Marín, Jorge Carrillo-de-Albornoz, Laura Plaza
• Leveraging MiniLMv2 Pipelines for EXIST2023 1037-1043
  Alexandru Petrescu
• LSTM-Attention Architecture for Online Bilingual Sexism Detection 1044-1059
  Srinivasa Ravi, Siddharth Kelkar, Anand Kumar Madasamy
• ZaRa-IU-NLP at EXIST 2023 - Sexism Identification: Specialized or Generalized? 1060-1066
  Zackary Leech, Ravi Regulagedda, Sandra Kübler
• IimasGIL_NLP@EXIST2023: Unveiling Sexism on Twitter with Fine-tuned Transformers 1067-1082
  Andrea Sanchez-Urbina, Helena Gómez-Adorno, Gemma Bel-Enguix, Vianey Rodríguez-Figueroa, Angela Monge-Barrera
• Efficient Multilingual Sexism Detection via Large Language Model Cascades 1083-1090
  Lin Tian, Nannan Huang, Xiuzhen Zhang
• Integrating Annotator Information in Transformer Fine-tuning for Sexism Detection 1091-1106
  María Estrella Vallecillo-Rodríguez, Flor Miriam Plaza-del-Arco, Luis Alfonso Ureña-López, María Teresa Martín-Valdivia, Arturo Montejo-Ráez
• Leveraging GPT-2 for Automated Classification of Online Sexist Content 1107-1122
  Advaitha Vetagiri, Prottay Kumar Adhikary, Partha Pakray, Amitava Das

Intelligent Disease Progression Prediction at CLEF (iDPP@CLEF)

• Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge 1123-1164
  Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro
• Maximum Likelihood Estimation with Deep Learning for Multiple Sclerosis Progression Prediction 1165-1185
  Tsvetan Asamov, Petar Ivanov, Anna Aksenova, Dimitar Taskov, Svetla Boytcheva
• Investigating the Impact of Environmental Data on ALS Prognosis with Survival Analysis 1186-1198
  Ruben Branco, Diogo F. Soares, Andreia S. Martins, Joana Barros Valente, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos
• Survival Analysis for Multiple Sclerosis: Predicting Risk of Disease Worsening 1199-1209
  Ruben Branco, Joana Barros Valente, Andreia S. Martins, Diogo F. Soares, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos
• Predicting and Explaining Risk of Disease Worsening Using Temporal Features in Multiple Sclerosis 1210-1218
  Tommaso Mario Buonocore, Pietro Bosoni, Giovanna Nicora, Mahin Vazifehdan, Riccardo Bellazzi, Enea Parimbelli, Arianna Dagliati
• Baseline Machine Learning Approaches To Predict Multiple Sclerosis Disease Progression 1219-1232
  Alessandro Guazzo, Isotta Trescato, Enrico Longato, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo
• Predicting Risk of Multiple Sclerosis Worsening 1233-1245
  Marek Hanzl, Lukáš Picek
• Air Pollution Profiling through Patient Stratification: Study of ALS Staging Systems Usefulness in Facilitating Data-driven Disease Subtyping and Discovery of Hazardous Ambient Air Pollutants 1246-1271
  Mohamed Chiheb Karray
• Time-to-Event Interpretable Machine Learning for Multiple Sclerosis Worsening Prediction: Results from iDPP@CLEF 2023 1272-1285
  Angela Lombardi, Maria Luigia Natalia De Bonis, Giuseppe Fasano, Alessia Sportelli, Tommaso Colafiglio, Domenico Lofù, Paolo Sorino, Fedelucio Narducci, Eugenio Di Sciascio, Tommaso Di Noia
• HULAT@IDDP CLEF 2023: Intelligent Prediction of Disease Progression in Multiple Sclerosis Patients 1286-1297
  Alberto Ramos, Paloma Martínez, Israel González-Carrasco
• Multiple Sclerosis Survival Prediction Results from DSM-COMPBIO UNITO 1298-1304
  Ivan Rossi, Giovanni Birolo, Piero Fariselli

Multimedia Retrieval Challenge in CLEF (ImageCLEF)

• Overview of ImageCLEFmedical GANs 2023 Task – Identifying Training Data “Fingerprints” in Synthetic Biomedical Images Generated by GANs for Medical Image Security 1305-1315
  Alexandra-Georgiana Andrei, Ahmedkhan Radzhabov, Ioan Coman, Vassili Kovalev, Bogdan Ionescu, Henning Müller
• Overview of ImageCLEFmedical 2023 – Medical Visual Question Answering for Gastrointestinal Tract 1316-1327
  Steven Hicks, Andrea Storås, Pål Halvorsen, Thomas de Lange, Michael Riegler, Vajira Thambawita
• Overview of ImageCLEFmedical 2023 – Caption Prediction and Concept Detection 1328-1346
  Johannes Rückert, Asma Ben Abacha, Alba G. Seco de Herrera, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir, Henning Schäfer, Henning Müller, Christoph M. Friedrich
• Overview of the MEDIQA-Sum Task at ImageCLEF 2023: Summarization and Classification of Doctor-Patient Conversations 1347-1360
  Wen-wai Yim, Asma Ben Abacha, Griffin Adams, Neal Snider, Meliha Yetisgen
• Overview of ImageCLEFfusion 2023 Task - Testing Ensembling Methods in Diverse Scenarios 1361-1366
  Liviu-Daniel ?tefan, Mihai Gabriel Constantin, Mihai Dogariu, Bogdan Ionescu
• TREDENCE at MEDIQA-Sum 2023: Clinical Note Generation from Doctor Patient Conversation using Utterance Segmentation and Question-Answer Driven Abstractive Summarization 1367-1378
  Vaibhav Adwani, Mohammed Sameer Khan, Ankush Chopra
• AIMultimediaLab at ImageCLEFmedical GANs 2023: Determining "Fingerprints" of Training Data in Generated Synthetic Images 1379-1386
  Alexandra-Georgiana Andrei, Bogdan Ionescu
• Multi-stage Medical Image Captioning using Classification and CLIP 1387-1395
  Masaki Aono, Hiroki Shinoda, Tetsuya Asakawa, Kazuki Shimizu, Takuya Togawa, Takuyuki Komoda
• Real and Generated Image Classification using Multi-stage Transfer Learning 1396-1402
  Tetsuya Asakawa, Hiroki Shinoda, Takuya Togawa, Kazuki Shimizu, Masaki Aono
• Efficient Fusion Techniques for Result Diversification and Image Interestingness Tasks 1403-1414
  Prabavathy Balasundaram, G Gnana Sai, Kishore N, Olirva M, Makesh Vaibhav A.G, Naren Srinivasan Murali, Parlapalli Sai Harshith
• Correlating Biomedical Image Fingerprints between GAN-generated and Real Images using a ResNet Backbone with ML-based Downstream Comparators and Clustering: ImageCLEFmed GANs, 2023 1415-1422
  Haricharan Bharathi, Anirudh Bhaskar, Vishal Venkataramani, Karthik Desingu, Lekshmi Kalinathan
• UETCorn at MEDIQA-Sum 2023: Template-based Summarization for Clinical Note Generation from Doctor-Patient Conversation 1423-1432
  Duy-Cat Can, Quoc-An Nguyen, Binh-Nguyen Nguyen, Minh-Quang Nguyen, Khanh-Vinh Nguyen, Trung-Hieu Do, Hoang-Quynh Le
• Finding the Source Images From the Generated Images with Contrastive Learning Methods 1433-1439
  Shitong Cao, Xiaobing Zhou
• StellEllaStars at MEDIQA-Sum 2023: Exploring Transformer-Based models for Dialogue2Topic Classification 1440-1449
  Chi-Yun Chang, Jiaqi Li, Shivangi Kumar, V.G. Vinod Vydiswaran
• Language-based Colonoscopy Image Analysis with Pretrained Neural Networks 1450-1461
  Patrycja Cieplicka, Julia Klos, Maciej Morawski, Jaroslaw Opala
• Media Interestingness Prediction in ImageCLEFfusion 2023 with Dense Architecture-based Ensemble & Scaled Gradient Boosting Regressor Model 1462-1466
  Md. Ismail Siddiqi Emon, Md Mahmudur Rahman
• Analyzing the Similarity between Artificial and Training Images in Generative Models: The PicusLabMed Contribution 1467-1477
  Michela Gravina, Stefano Marrone, Carlo Sansone
• A Dual of Stacked Attention Networks (SAN’s) and VGG-16 Model-Based Visual Question Answering Evaluation 1478-1487
  Rohit Raj Gunti, Abebe Rorissa
• HuskyScribe at MEDIQA-Sum 2023: Summarizing Clinical Dialogues with Transformers 1488-1509
  Bin Han, Haotian Zhu, Sitong Zhou, Sofia Ahmed, Md. Mushfiqur Rahman, Fei Xia, Kevin Lybarger
• Concept Detection and Caption Prediction in ImageCLEFmedical Caption 2023 with Convolutional Neural Networks, Vision and Text-to-Text Transfer Transformers 1510-1523
  Md. Rakibul Hasan, Oyebisi Layode, Md Mahmudur Rahman
• AUEB NLP Group at ImageCLEFmedical Caption 2023 1524-1548
  Panagiotis Kaliosis, Georgios Moschovis, Foivos Charalampakos, John Pavlopoulos, Ion Androutsopoulos
• SSNdhanyadivyakavitha at MEDIQA-Sum 2023: Medical Dialogue Summarization using Linear Support Vector Classification Technique 1549-1557
  Dhanya Krishnan, Divya Srinivasan, Kavitha Srinivasan
• IUST_NLPLAB at ImageCLEFmedical Caption Tasks 2023 1558-1570
  Yasaman Lotfollahi, Melika Nobakhtian, Malihe Hajihosseini, Sauleh Eetemadi
• UIT-Saviors at MEDVQA-GI 2023: Improving Multimodal Learning with Image Enhancement for Gastrointestinal Visual Question Answering 1571-1587
  Triet M. Thai, Anh T. Vo, Hao K. Tieu, Linh N.P. Bui, Thien T.B. Nguyen
• GAN-ISI: Generative Adversarial Networks Image Source Identification Using Texture Analysis 1588-1595
  Mehdi Mehdipour Ghazi, Mostafa Mehdipour Ghazi
• Evaluating Privacy on Synthetic Images Generated using GANs: Contributions of the VCMI Team to ImageCLEFmedical GANs 2023 1596-1610
  Helena Montenegro, Pedro Neto, Cristiano Patrício, Isabel Rio-Torto, Tiago Gonçalves, Luís F. Teixeira
• A Concise Model for Medical Image Captioning 1611-1619
  Aaron Nicolson, Jason Dowling, Bevan Koopman
• SSN MLRG at ImageCLEFmedical Caption 2023: Automatic Concept Detection and Caption Prediction using ConceptNet and Vision Transformer 1620-1626
  Sheerin Sitara Noor Mohamed, Kavitha Srinivasan
• SSN MLRG at MEDIQA-SUM 2023: Automatic Text Summarization using Support Vector Machine and RoBERTa 1627-1632
  Sheerin Sitara Noor Mohamed, Kavitha Srinivasan
• SSN MLRG at MEDVQA-GI 2023: Visual Question Generation and Answering using Transformer based Pre-trained Models 1633-1640
  Sheerin Sitara Noor Mohamed, Kavitha Srinivasan, Raghuraman Gopalsamy
• Concept Detection and Caption Prediction from Medical Images using Gradient Boosted Ensembles and Deep Learning 1641-1652
  Mirunalini Palaniappan, Haricharan Bharathi, Eeswara Anvesh Chodisetty, Anirudh Bhaskar, Karthik Desingu
• Detecting Concepts and Generating Captions from Medical Images: Contributions of the VCMI Team to ImageCLEFmedical Caption 2023 1653-1667
  Isabel Rio-Torto, Cristiano Patrício, Helena Montenegro, Tiago Gonçalves, Jaime S. Cardoso
• PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records 1668-1679
  Viktor Schlegel, Hao Li, Yuping Wu, Anand Subramanian, Thanh-Tung Nguyen, Abhinav Ramesh Kashyap, Daniel Beck, Xiaojun Zeng, Riza Theresa Batista-Navarro, Stefan Winkler, Goran Nenadic
• Team Cadence at MEDIQA-Sum 2023: Using ChatGPT as a Data Augmentation Tool for Classifying Clinical Dialogue 1680-1687
  Ashwyn Sharma, David I. Feldman
• KDE Lab at ImageCLEFmedical Caption 2023 1688-1701
  Hiroki Shinoda, Masaki Aono, Tetsuya Asakawa, Kazuki Shimizu, Takuyuki Komoda, Takuya Togawa
• DMK-SSN at ImageCLEF 2023 Medical: Controlling the Quality of Synthetic Medical Images Created via GANs using Machine Learning and Image Hashing Techniques 1702-1710
  Dhivya Subburam, Shriram M SathyaNarayanan, Bhavana Anand, Kavitha Srinivasan, Mohanavalli Subramaniam
• MLRG-JBTTM at MEDIQA-Sum 2023: Dialogue2Topic Classification 1711-1719
  Harshida Sujatha Palaniraj, Keerthan Vinod, Mohith Adluru, Bhuvana Jayaraman, Mirnalinee TT
• SuryaKiran at MEDIQA-Sum 2023: Leveraging LoRA for Clinical Dialogue Summarization 1720-1735
  Kunal Suri, Prakhar Mishra, Saumajit Saha, Atul Singh
• BIT Mesra at ImageCLEF 2023: Fusion of Blended Image and Text Features for Medical VQA 1736-1743
  Sushmita Upadhyay, Sanjaya Shankar Tripathy
• Adapting Pre-Trained Visual and Language Models for Medical Image Question Answering 1744-1753
  Siqi Wang, Wenshuo Zhou, Yehui Yang, Haifeng Huang, Zhiyu Ye, Tong Zhang, Dalu Yang
• PCLmed at ImageCLEFmedical 2023: Customizing General-Purpose Foundation Models for Medical Report Generation 1754-1766
  Bang Yang, Asif Raza, Yuexian Zou, Tong Zhang
• Concept Detection and Image Caption Generation in Medical Imaging 1767-1775
  Varsha Yeshwanth, Pranith P, Lekshmi Kalinathan
• Transferring Pre-Trained Large Language-Image Model for Medical Image Captioning 1776-1784
  Wenshuo Zhou, Zhiyu Ye, Yehui Yang, Siqi Wang, Haifeng Huang, Rongjie Wang, Dalu Yang

Automatic Wordplay Analysis (JOKER)

• Overview of JOKER 2023 Automatic Wordplay Analysis Task 1 – Pun Detection 1785-1803
  Liana Ermakova, Tristan Miller, Anne-Gwenn Bosser, Victor Manuel Palma Preciado, Grigori Sidorov, Adam Jatowt
• Overview of JOKER 2023 Automatic Wordplay Analysis Task 2 – Pun Location and Interpretation 1804-1817
  Liana Ermakova, Tristan Miller, Anne-Gwenn Bosser, Victor Manuel Palma Preciado, Grigori Sidorov, Adam Jatowt
• Overview of JOKER 2023 Automatic Wordplay Analysis Task 3 – Pun Translation 1818-1827
  Liana Ermakova, Tristan Miller, Anne-Gwenn Bosser, Victor Manuel Palma Preciado, Grigori Sidorov, Adam Jatowt
• Exploring Humor in Natural Language Processing: A Comprehensive Review of JOKER Tasks at CLEF Symposium 2023 1828-1837
  Aftab Anjum, Nikolaus Lieberum
• CLEF 2023 JOKER Task 2 : Using Chat GPT for Pun Location and Interpretation 1838-1845
  Océane Brunelière, Constance Germann, Keith Salina
• AKRaNLU @ CLEF JOKER 2023: Using Sentence Embeddings and Multilingual Models to Detect and Interpret Wordplay 1846-1853
  Ryan Rony Dsilva
• UBO Team @ CLEF JOKER 2023 Track For Task 1, 2 and 3 - Applying AI Models In Regards To Pun Translation 1854-1861
  Quentin Dubreuil
• BU-Pier Team @ CLEF JOKER 2023 Open Task: Slip of the Tongue Generation to Improve Social Interaction with Virtual Agents 1862-1867
  Loïc Glemarec, Fred Charles
• CLEF2023’ JOKER 1868-1874
  Julia Komorowska, Iva Catipovic, Darko Vujica
• CLEF 2023 JOKER Tasks 2 and 3: Using NLP Models for Pun Location, Interpretation and Translation 1875-1880
  Felix Ohnesorge, Mari Angeles Gutierrez, Julia Plichta
• NLPalma @ CLEF 2023 JOKER: A BLOOMZ and BERT Approach for Wordplay Detection and Translation 1881-1887
  Victor Manuel Palma Preciado, Carolina Palma Preciado, Grigori Sidorov
• Does AI Have a Sense of Humor? CLEF 2023 JOKER Tasks 1, 2 and 3: Using BLOOM, GPT, SimpleT5, and More for Pun Detection, Location, Interpretation and Translation 1888-1908
  Olga Popova, Petra Dadic
• CLEF 2023 JOKER Task 1, 2, 3: Pun Detection, Pun Interpretation, and Pun Translation 1909-1917
  Antonela Prnjak, Dennis R. Davari, Kristina Schmitt
• Innsbruck @ JOKER2023 Task 1: Data Augmentation Techniques for Humor Recognition in Text 1918-1924
  Stefan Reicho, Adam Jatowt
• Why Sentiment Analysis is a Joke with JOKER data? Word-Level and Interpretation Analysis (CLEF 2023 JOKER Task 2) 1925-1933
  Tremaine Thomas-Young

Multimedia Retrieval in Nature (LifeCLEF)

• Overview of BirdCLEF 2023: Automated Bird Species Identification in Eastern Africa 1934-1942
  Stefan Kahl, Tom Denton, Holger Klinck, Hendrik Reers, Francis Cherutich, Hervé Glotin, Hervé Goëau, Willem-Pier Vellinga, Robert Planqué, Alexis Joly
• Overview of FungiCLEF 2023: Fungi Recognition Beyond 1/0 Cost 1943-1953
  Lukáš Picek, Milan Šulc, Rail Chamidullin, Jirí Matas
• Overview of GeoLifeCLEF 2023: Species Composition Prediction with High Spatial Resolution at Continental Scale Using Remote Sensing 1954-1971
  Christophe Botella, Benjamin Deneu, Diego Marcos Gonzalez, Maximilien Servajean, Théo Larcher, César Leblanc, Joachim Estopinan, Pierre Bonnet, Alexis Joly
• Overview of PlantCLEF 2023: Image-based Plant Identification at Global Scale 1972-1981
  Hervé Goëau, Pierre Bonnet, Alexis Joly
• Overview of SnakeCLEF 2023: Snake Identification in Medically Important Scenarios 1982-1995
  Lukáš Picek, Rail Chamidullin, Marek Hrúz, Andrew M. Durso
• Metric-Weighted Ensemble Focal Loss for Snake Species Identification 1996-2006
  Aarti Balana
• Joint Feature Learning of Image Data with Embedded Metadata to Leverage Snake Species Classification 2007-2034
  Benjamin Bracke, Mohammadreza Bagherifar, Louise Bloch, Christoph M. Friedrich
• Deep Learning for Large-Scale Plant Classification: NEUON Submission to PlantCLEF 2023 2035-2042
  Sophia Chulif, Yang Loong Chang, Sue Han Lee
• Acoustic Bird Species Recognition at BirdCLEF 2023: Training Strategies for Convolutional Neural Network and Inference Acceleration using OpenVINO 2043-2050
  Lihang Hong
• A Deep Learning based Solution to FungiCLEF2023 2051-2059
  Feiran Hu, Peng Wang, Yangyang Li, Chenlong Duan, Zijian Zhu, Yong Li, Xiu-Shen Wei
• Watch out Venomous Snake Species: A Solution to SnakeCLEF2023 2060-2070
  Feiran Hu, Peng Wang, Yangyang Li, Chenlong Duan, Zijian Zhu, Fei Wang, Faen Zhang, Yong Li, Xiu-Shen Wei
• Bird Species Recognition using Convolutional Neural Networks with Attention on Frequency Bands 2071-2079
  Mario Lasseck
• Classic Approaches to Bird Song Classification 2080-2090
  Mihai-Dimitrie Minu?, Cristian Simionescu, Adrian Iftene
• Transfer Learning with Semi-Supervised Dataset Annotation for Birdcall Classification 2091-2106
  Anthony Miyaguchi, Nathan Zhong, Murilo Gustineli, Chris Hayduk
• Reading the Robot Mind – Presenting Internal Data Flow Within an AI for Classification of Bird Sounds in a Format Familiar to Subject Matter Experts 2107-2121
  Paul Nussbaum
• Entropy-guided Open-set Fine-grained Fungi Recognition 2122-2136
  Huan Ren, Han Jiang, Wang Luo, Meng Meng, Tianzhu Zhang
• Metaformer Model with ArcFaceLoss and Contrastive Learning for SnakeCLEF2023 Fine-Grained Classification 2137-2148
  Zhennan Shi, Huazhen Chen, Chang Liu, Jun Qiu
• Leverage Samples with Single Positive Labels to Train CNN-based Models For Multi-label Plant Species Prediction 2149-2158
  Huy Quang Ung, Ryoichi Kojima, Shinya Wada
• Optimizing Fine-Grained Fungi Classification for Diverse Application-Oriented Open-Set Metrics 2159-2167
  Stefan Wolf, Jürgen Beyerer
• PlantCLEF2023: A Bigger Training Dataset Contributes More than Advanced Pretraining Methods for Plant Identification 2168-2180
  Mingle Xu, Sook Yoon, Chenmou Wu, Jeonghyun Baek, Dong Sun Park

Longitudinal Evaluation of Model Performance (LongEval)

• Extended Overview of the CLEF-2023 LongEval Lab on Longitudinal Evaluation of Model Performance 2181-2203
  Rabab Alkhalifa, Iman Bilal, Hsuvas Borkakoty, Jose Camacho-Collados, Romain Deveaud, Alaa El-Ebshihy, Luis Espinosa-Anke, Gabriela Nicole González-Sáez, Petra Galušcáková, Lorraine Goeuriot, Elena Kochkina, Maria Liakata, Daniel Loureiro, Philippe Mulhem, Florina Piroi, Martin Popel, Christophe Servan, Harish Tayyar Madabushi, Arkaitz Zubiaga
• SEUNIPD@CLEF: Team JIHUMING on Enhancing Search Engine Performance with Character N-Grams, Query Expansion, and Named Entity Recognition 2204-2221
  Isil Atabek, Huimin Chen, Jesús Moncada-Ramírez, Nicolò Santini, Giovanni Zago, Nicola Ferro
• SEUPD@CLEF: Team GWCA on Longitudinal Evaluation of IR Systems by Using Query Expansion and Learning To Rank 2222-2238
  Leonardo Bellin, Antonino Andrea Carè, Marco Martini, Maria Teresa Pepaj, Matteo Salvalaio, Andrea Segala, Mariafiore Tognon, Nicola Ferro
• SEUPD@CLEF: RAFJAM on Longitudinal Evaluation of Model Performance 2239-2251
  Alvise Bolzonella, Riccardo Broetto, Marco Gasparini, Farhad Sadat, Nicola Ferro
• SEUPD@CLEF: Team FADERIC on A Query Expansion and Reranking Approach for the LongEval Task 2252-2280
  Enrico Bolzonello, Christian Marchiori, Daniele Moschetta, Riccardo Trevisiol, Fabio Zanini, Nicola Ferro
• SEUPD@CLEF: Team NEON. A Memoryless Approach To Longitudinal Evaluation 2281-2305
  Simone Bortolin, Gioele Ceccon, Gil Czaczkes, Alessandra Pastore, Pietro Renna, Giovanni Zerbo, Nicola Ferro
• SEUPD@CLEF: Team Squid on LongEval-Retrieval 2306-2337
  Vittorio Cardillo, Alberto Dorizza, Mattia Maglie, Dario Mameli, Gianluca Rossi, Michele Russo, Nicola Ferro
• SEUPD@CLEF: Team DARDS - IR System for Short and Long Term Retrieval 2338-2367
  Daniel Carlesso, Riccardo Gobbo, Simone Merlo, Angela Pomaro, Diego Spinosa, Nicola Ferro
• SEUPD@CLEF: Team CLOSE on Temporal Persistence of IR Systems’ Performance 2368-2395
  Gianluca Antolini, Nicola Boscolo, Mirco Cazzaro, Marco Martinelli, Seyedreza Safavi, Farzad Shami, Nicola Ferro
• SEUPD@CLEF: Team HIBALL on Incremental Information Retrieval System with RRF and BERT 2396-2415
  Andrea Ceccato, Luca Fabbian, Bor-Woei Huang, Irfan Ullah Khan, Harjot Singh, Nicola Ferro
• SEUPD@CLEF: Team QEVALS on Information Retrieval Adapted to the Temporal Evolution of Web Documents 2416-2431
  Enrico D'Alberton, Saverio Fincato, Vaidas Lenartavicius, Laura Pallante, Yi Jian Qiu, Nicola Ferro
• Open Web Search at LongEval 2023: Reciprocal Rank Fusion on Automatically Generated Query Variants 2432-2440
  Maik Fröbe, Gijs Hendriksen, Arjen P. de Vries, Martin Potthast
• Evaluating Temporal Persistence Using Replicability Measures 2441-2457
  Jüri Keller, Timo Breuer, Philipp Schaer
• The Temporal Persistence of Generative Language Models in Sentiment Analysis 2458-2468
  Pablo Medina-Alias, Özgür Simsek
• Keeping in Time: Adding Temporal Context to Sentiment Analysis Models 2469-2475
  Dean Ninalga

Lab on Digital Text Forensics and Stylometry (PAN)

• Overview of the Authorship Verification Task at PAN 2023 2476-2491
  Efstathios Stamatatos, Krzysztof Kredens, Piotr Pezik, Annina Heini, Janek Bevendorff, Benno Stein, Martin Potthast
• Profiling Cryptocurrency Influencers with Few-shot Learning 2492-2512
  Mara Chinea-Rios, Ian Borrego-Obrador, Marc Franco-Salvador, Francisco Rangel, Paolo Rosso
• Overview of the Multi-Author Writing Style Analysis Task at PAN 2023 2513-2522
  Eva Zangerle, Maximilian Mayerl, Martin Potthast, Benno Stein
• Overview of the Trigger Detection Task at PAN 2023 2523-2536
  Matti Wiegmann, Magdalena Wolska, Martin Potthast, Benno Stein
• Leveraging Large Language? Models with Multiple Loss Learners for Few-Shot Author Profiling 2539-2551
  Hamed Babaei Giglou, Mostafa Rahgouy, Jennifer D'Souza, Milad Molazadeh Oskuee, Hadi Bayrami Asl Tekanlou, Cheryl D Seals
• A Dual-model Classification Based on RoBERTa for Trigger Detection 2552-2556
  Guiyuan Cao, Zhongyuan Han, Haojie Cao, Ximin Huang, Zhengqiao Zeng, Yaozu Tan, Jiyin Cai, Xu Sun
• Trigger Warning Labeling with RoBERTa and Resampling for Distressing Content Detection 2557-2561
  Haojie Cao, Zhongyuan Han, Guiyuan Cao, Ruihao Zhu, Yongqi Liang, Siman Liu, Minhua Huang, Haihao Yu
• A Writing Style Embedding Based on Contrastive Learning for Multi-Author Writing Style Analysis 2562-2567
  Haoyang Chen, Zhongyuan Han, Zengyao Li, Yong Han
• Using BERT to Profiling Cryptocurrency Influencers 2568-2573
  Daniel Yacob Espinosa, Grigori Sidorov
• FoSIL at PAN’23: Trigger Detection with a Two Stage Topic Classifier 2574-2587
  Jenny Felser, Christoph Demus, Dirk Labudde, Michael Spranger
• Profiling Cryptocurrency Influencers with Few-shot Learning 2588-2598
  Isabel Ferri-Molla, Jaume Santamaria-Jorda
• Profiling Cryptocurrency Influencers with Sentence Transformers 2599-2607
  Kavya Girish, Asha Hegde, Fazlourrahman Balouchzahi, Shashirekha Hosahalli Lakshmaiah
• A Contrastive Learning of Sample Pairs for Authorship Verification 2608-2612
  Mingcan Guo, Zhongyuan Han, Haoyang Chen, Haoliang Qi
• Enhancing Writing Style Change Detection using Transformer-based Models and Data Augmentation 2613-2621
  Ahmad Hashemi, Wei Shi
• Trigger Detection in Social Media Text 2622-2628
  Asha Hegde, Fazlourrahman Balouchzahi, Kavya G, Hosahalli Shashirekha Lakshmaiah
• Encoded Classifier Using Knowledge Distillation for Multi-Author Writing Style Analysis 2629-2634
  Mingjie Huang, Zhaohao Huang, Leilei Kong
• Authorship Verification Based on CoSENT 2635-2639
  Zhaohao Huang, Leilei Kong, Mingjie Huang
• Enhancing Authorship Verification using Sentence-Transformers 2640-2651
  Momen Ibrahim, Ahmed Akram, Mohammed Radwan, Rana Ayman, Mustafa Abd-El-Hameed, Nagwa El-Makky, Marwan Torki
• Authorship Verification Machine Learning Methods For Style Change Detection In Texts 2652-2658
  Gianni X. Jacobo, Valeria Dehesa-Corona, Ariel D. Rojas-Reyes, Helena Gómez-Adorno
• ARC-NLP at PAN 2023: Transition-Focused Natural Language Inference for Writing Style Detection 2659-2668
  Izzet Emre Kucukkaya, Umitcan Sahin, Cagri Toraman
• UZH at PAN-2023: Profiling Cryptocurrency Influencers using Ensemble of Language Models 2669-2678
  Abhinav Kumar, Le Hoang Minh Trinh, Afshan Anam Saeed
• Reshape or Update? Metric Learning and Fine-tuning for Low-Resource Influencer Profiling 2679-2690
  Roberto Labadie Tamayo, Areg Mikael Sarvazyan
• Author Verification Of Text Fragments Based On The Bert Model 2691-2694
  Ji Li, Qianjin Zhang, Mingjie Huang
• Profiling Cryptocurrency Influencers With Few-shot Learning via Contrastive Learning 2695-2701
  Zengyao Li, Zhongyuan Han, Jiyin Cai, Zhijian Huang, Shaohua Huang, Leilei Kong
• Text-Segment Interaction for Authorship Verification using BERT-based Classification 2702-2707
  Xurong Liu, Leilei Kong, Mingjie Huang
• Text Enrichment with Japanese Language to Profile Cryptocurrency Influencers 2708-2716
  Francesco Lomonaco, Marco Siino, Maurizio Tesconi
• Application of R-Drop in Authorship Verification 2717-2721
  Jiajun Lv, Yong Han, Qian Dong
• Profiling Cryptocurrency Influencers using Few-shot Learning 2722-2733
  Hamna Muslihuddeen, Pallapothula Sathvika, Shalaka Sankar, Shreya Ostwal, Anand Kumar M
• Contrastive Learning for Authorship Verification using BERT and Bi-LSTM in a Siamese Architecture 2734-2741
  Panagiotis Petropoulos
• Authorship Verification Based on SimCSE 2742-2746
  Yong Qiu, Haoliang Qi, Yong Han, Kaicheng Huang
• ARC-NLP at PAN 2023: Hierarchical Long Text Classification for Trigger Detection 2747-2757
  Umitcan Sahin, Izzet Emre Kucukkaya, Cagri Toraman
• A Multi-Feature Custom Classification Approach to Authorship Verification 2758-2762
  Riya Sanjesh, Alamelu Mangai
• XLNet with Data Augmentation to Profile Cryptocurrency Influencers 2763-2771
  Marco Siino, Ilenia Tinnirello
• Profiling Cryptocurrency Influencers with Few-Shot Learning Using Data Augmentation and ELECTRA 2772-2781
  Marco Siino, Maurizio Tesconi, Ilenia Tinnirello
• Siamese Networks in Trigger Detection Task 2782-2786
  Yunsen Su, Yong Han, Haoliang Qi
• Stylometric and Neural Features Combined Deep Bayesian Classifier for Authorship Verification 2787-2794
  Yitao Sun, Svetlana Afanaseva, Kailash Patil
• Heterogeneous-Graph Convolutional Network for Authorship Verification 2795-2802
  Andric Valdez-Valenzuela, Jorge Alfonso Martinez-Galicia, Helena Gómez-Adorno
• Few Shot Profiling of Cryptocurrency Influencers using Natural Language Inference & Large Language Models 2803-2816
  Emilio Villa-Cueva, Jorge Miguel Valles-Silva, Adrian Pastor Lopez-Monroy, Fernando Sanchez-Vega, Jesus Roberto Lopez-Santillan
• Supervised Contrastive Learning for Multi-Author Writing Style Analysis 2817-2822
  Zhanhong Ye, Changle Zhong, Haoliang Qi, Yong Han

Automatic Simplification of Scientific Texts (SimpleText)

• Overview of the CLEF 2023 SimpleText Task 1: Passage Selection for a Simplified Summary 2823-2834
  Éric Sanjuan, Stéphane Huet, Jaap Kamps, Liana Ermakova
• Overview of the CLEF 2023 SimpleText Task 2: Difficult Concept Identification and Explanation 2835-2854
  Liana Ermakova, Hosein Azarbonyad, Sarah Bertin, Olivier Augereau
• Overview of the CLEF 2023 SimpleText Task 3: Simplification of Scientific Texts 2855-2875
  Liana Ermakova, Sarah Bertin, Helen McCombie, Jaap Kamps
• UZH_Pandas at SimpleText@CLEF-2023: Alpaca LoRA 7B and LENS Model Selection for Scientific Literature Simplification 2876-2898
  Pascal Severin Andermatt, Tobias Fankhauser
• Automatic Simplification of Scientific Texts using Pre-trained Language Models: A Comparative Study at CLEF Symposium 2023 2899-2907
  Aftab Anjum, Nikolaus Lieberum
• Comparing ChatGPT’s and Human Evaluation of Scientific Texts’ Translations from English to Portuguese Using Popular Automated Translators 2908-2917
  Sílvia Araújo, Micaela Aguiar
• Scientific Simplification, the Limits of ChatGPT. 2918-2922
  Sarah Bertin
• Elsevier at SimpleText: Passage Retrieval by Fine-tuning GPL on Scientific Documents 2923-2934
  Artemis Capari, Hosein Azarbonyad, Georgios Tsatsaronis, Zubair Afzal
• CLEF 2023 SimpletText Tasks 2 and 3: Enhancing Language Comprehension: Addressing Difficult Concepts and Simplifying Scientific Texts Using GPT, BLOOM, KeyBert, Simple T5 and More 2935-2957
  Petra Dadic, Olga Popova
• CLEF2023 SimpleText Task 2, 3: Identification and Simplification of Difficult Terms 2958-2968
  Dennis R. Davari, Antonela Prnjak, Kristina Schmitt
• UBO Team @ CLEF SimpleText 2023 Track for Task 2 and 3 - Using IA models to simplify Scientific Texts 2969-2978
  Quentin Dubreuil
• Domain Context-centered Retrieval for the Content Selection task in the Simplification of Scientific Literature 2979-2986
  Óscar E. Mendoza, Gabriella Pasi
• Text Simplification of Scientific Texts for Non-Expert Readers 2987-2998
  Björn Engelmann, Fabian Haak, Christin Katharina Kreutz, Narjes Nikzad Khasmakhi, Philipp Schaer
• An Evaluation of MUSS and T5 Models in Scientific Sentence Simplification: A Comparative Study 2999-3006
  Running Hou, Xinyi Qin
• University of Amsterdam at the CLEF 2023 SimpleText Track 3007-3016
  Roos Hutter, Jop Sutmuller, Mary Adib, David Rau, Jaap Kamps
• AIIR and LIAAD Labs Systems for CLEF 2023 SimpleText 3017-3026
  Behrooz Mansouri, Shea Durgin, Sj Franklin, Sean Fletcher, Ricardo Campos
• CLEF 2023: Scientific Text Simplification and General Audience 3027-3032
  Felix Ohnesorge, Mari Ángeles Gutiérrez, Julia Plichta
• SINAI Participation in SimpleText Task 2 at CLEF 2023: GPT-3 in Lexical Complexity Prediction for General Audience 3033-3044
  Jenny Ortiz-Zambrano, César Espin-Riofrio, Arturo Montejo-Ráez
• NLPalma @ CLEF 2023 SimpleText: BLOOMZ and BERT for Complexity and Simplification Task 3045-3049
  Victor Manuel Palma Preciado, Carolina Palma Preciado, Grigori Sidorov
• CLEF2023 SimpleText 3050-3056
  Darko Vujica, Iva Catipovic, Julia Komorowska
• A Prompt Engineering Approach to Scientific Text Simplification: CYUT at SimpleText2023 Task3 3057-3064
  Shih-Hung Wu, Hong-Yi Huang

Argument Retrieval (Touché)

• Overview of Touché 2023: Argument and Causal Retrieval 3065-3089
  Alexander Bondarenko, Maik Fröbe, Johannes Kiesel, Ferdinand Schlatt, Valentin Barriere, Brian Ravenet, Léo Hemamou, Simon Luck, Jan Heinrich Reimer, Benno Stein, Martin Potthast, Matthias Hagen
• Silver Surfer team at Touché task 4: Testing Data Augmentation and Label Propagation for Multilingual Stance Detection 3090-3097
  Jorge Avila, Alvaro Rodrigo, Roberto Centeno
• Neville Longbottom at Touché 2023: Image Retrieval for Arguments using ChatGPT, CLIP and IBM Debater 3098-3103
  Daria Elagina, Bernd-Albrecht Heizmann, Max Koch, Gustav Lahmann, Christian Ortlepp
• Evidence Retrieval for Causal Questions Using Query Expansion And Reranking 3104-3110
  Aron Gaden, Niklas Rausch, Bruno Reinhold, Lukas Zeit-Altpeter
• Jean-Luc Picard at Touché 2023: Comparing Image Generation, Stance Detection and Feature Matching for Image Retrieval for Arguments 3111-3118
  Max Moebius, Maximilian Enderling, Sarah T. Bachinger
• Argument Quality Prediction for Ranking Documents 3119-3130
  Moritz Plenz, Raphael Buchmüller, Alexander Bondarenko
• Queen of Swords at Touché 2023: Intra-Multilingual Multi-Target Stance Classification using BERT 3131-3138
  Karla Schäfer