CLEF 2024
CLEF 2024 Working Notes

Table of Contents

• Preface
  This volume contains the 339 working notes that were peer-reviewed and accepted for publication at CLEF 2024. Out of these, 37 are overviews of the labs and tasks, while 302 are the participants' working notes.

BioASQ: Large-scale Biomedical Semantic Indexing and Question Answering

• Overview of BioASQ Tasks 12b and Synergy12 in CLEF20241-7
  Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara, Georgios Paliouras
  
• Overview of MultiCardioNER task at BioASQ 2024 on Medical Specialty and Language Adaptation of Clinical NER Systems for Spanish, English and Italian8-27
  Salvador Lima-López, Eulalia Farre-Maduell, Jan Rodríguez-Miret, Miguel Rodríguez-Ortega, Livia Lilli, Jacopo Lenkowicz, Giovanna Ceroni, Jonathan Kossof, Anoop Shah, Anastasios Nentidis, Anastasia Krithara, Georgios Katsimpras, Georgios Paliouras, Martin Krallinger
  
• Overview of BioNNE Task on Biomedical Nested Named Entity Recognition at BioASQ 202428-34
  Vera Davydova, Natalia Loukachevitch, Elena Tutubalina
  
• Transformer-Based Disease and Drug Named Entity Recognition in Multilingual Clinical Texts: MultiCardioNER challenge35-46
  Anna Aksenova, Aleksis Datseris, Sylvia Vassileva, Svetla Boytcheva
  
• BIT.UA at BioASQ 12: From Retrieval to Answer Generation47-67
  Tiago Almeida, Richard A. A. Jonker, João Reis, João R. Almeida, Sérgio Matos
  
• LLM Fine-Tuning With Biomedical Open-Source Data68-77
  Christopher Anaya, Maria Fernandes, Francisco M Couto
  
• Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks78-98
  Samy Ateia, Udo Kruschwitz
  
• NCU-IISR: Enhancing Biomedical Question Answering with GPT-4 and Retrieval Augmented Generation in BioASQ 12b Phase B99-105
  Bing-Chen Chih, Jen-Chieh Han, Richard Tzong-Han Tsai
  
• Multilingual Clinical NER for Diseases and Medications Recognition in Cardiology Texts using BERT Embeddings106-116
  Manuela Daniela Danu, George Marica, Constantin Suciu, Lucian Mihai Itu, Oladimeji Farri
  
• Enhancing Biomedical Question Answering with Parameter-Efficient Fine-Tuning and Hierarchical Retrieval Augmented Generation117-129
  Yichen Gao, Licheng Zong, Yu Li
  
• Team NOVA LINCS @ BIOASQ12 MultiCardioNER Track: Entity Recognition with Additional Entity Types130-137
  Rodrigo Gonçalves, André Lamúrias
  
• Generative Large Language Models Augmented Hybrid Retrieval System for Biomedical Question Answering138-149
  Bor-Woei Huang
  
• BIT.UA at MultiCardioNER: Adapting a Multi-head CRF for Cardiology150-158
  Richard A. A. Jonker, Tiago Almeida, Sérgio Matos
  
• Comparative Analyses of Multilingual Drug Entity Recognition Systems for Clinical Case Reports In Cardiology159-167
  Chaeeun Lee, T. Ian Simpson, Joram M. Posma, Antoine D. Lain
  
• Enhancing Biomedical Document Ranking with Domain Knowledge Incorporation in a Multi-Stage Retrieval Approach.168-175
  Maël Lesavourey, Gilles Hubert
  
• MiBi at BioASQ 2024: Retrieval-Augmented Generation for Answering Biomedical Questions176-187
  Jan Heinrich Merker, Alexander Bondarenko, Matthias Hagen, Adrian Viehweger
  
• Farming Open LLMs for Biomedical Question Answering188-196
  Dimitra Panou, Alexandros C. Dimopoulos, Martin Reczko
  
• Nested Named Entity Recognition using Multilayer BERT-based Model197-206
  Hasin Rehana, Benu Bansal, Nur Bengisu Çam, Jie Zheng, Yongqun He, Arzucan Özgür, Junguk Hur
  
• Identifying Cardiological Disorders in Spanish via Data Augmentation and Fine-Tuned Language Models207-222
  Antonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato
  
• Cross-Linguistic Disease and Drug Detection in Cardiology Clinical Texts: Methods and Outcomes223-244
  Patrick Styll, Leonardo Campillos-Llanos, Wojciech Kusa, Allan Hanbury
  
• Biomedical Nested NER with Large Language Model and UMLS Heuristics245-252
  Wenxin Zhou
  
• Using Pretrained Large Language Model with Prompt Engineering to Answer Biomedical Questions253-268
  Wenxin Zhou, Thuy Hang Ngo
  
• HU-WBI at BioASQ12B Phase A: Exploring Rank Fusion of Dense Retrievers and Re-rankers269-275
  Oğuz Şerbetçi, Xing David Wang, Ulf Leser
  

CheckThat!: Predicting Check-Worthiness, Subjectivity, Persuasion, Roles and Authorities

• Overview of the CLEF-2024 CheckThat! Lab Task 1 on Check-Worthiness Estimation of Multigenre Content276-286
  Maram Hasanain, Reem Suwaileh, Sanne Weering, Chengkai Li, Tommaso Caselli, Wajdi Zaghouani, Alberto Barrón-Cedeño, Preslav Nakov, Firoj Alam
  
• Overview of the CLEF-2024 CheckThat! Lab Task 2 on Subjectivity in News Articles287-298
  Julia Maria Struß, Federico Ruggeri, Alberto Barrón-Cedeño, Firoj Alam, Dimitrov Dimitar, Andrea Galassi, Georgi Pachov, Ivan Koychev, Preslav Nakov, Melanie Siegel, Michael Wiegand, Maram Hasanain, Reem Suwaileh, Wajdi Zaghouani
  
• Overview of the CLEF-2024 CheckThat! Lab Task 3 on Persuasion Techniques299-310
  Jakub Piskorski, Nicolas Stefanovitch, Firoj Alam, Ricardo Campos, Dimitar Dimitrov, Alípio Jorge, Senja Pollak, Nikolay Ribin, Zoran Fijavž, Maram Hasanain, Purificação Silvano, Elisa Sartori, Nuno Guimarães, Ana Zwitter Vitez, Ana Filipa Pacheco, Ivan Koychev, Nana Yu, Preslav Nakov, Giovanni Da San Martino
  
• Overview of the CLEF-2024 CheckThat! Lab Task 5 on Rumor Verification using Evidence from Authorities311-320
  Fatima Haouari, Tamer Elsayed, Reem Suwaileh
  
• Overview of the CLEF-2024 CheckThat! Lab Task 6 on Robustness of Credibility Assessment with Adversarial Examples (InCrediblAE)321-338
  Piotr Przybyła, Ben Wu, Alexander Shvets, Yida Mu, Kim Cheng Sheang, Xingyi Song, Horacio Saggion
  
• IAI Group at CheckThat! 2024: Transformer models and data augmentation for checkworthy claim detection339-350
  Peter Røysland Aarnes, Vinay Setty, Petra Galuščáková
  
• DEFAULT at CheckThat! 2024: Retrieval Augmented Classification using Differentiable Top-K Operator for Rumor Verification based on Evidence from Authorities351-360
  Sayanta Adhikari, Himanshu Sharma, Rupa Kumari, Shrey Satapara, Maunendra Desarkar
  
• Nullpointer at CheckThat! 2024: Identifying Subjectivity from Multilingual Text Sequence361-368
  Md Rafiul Biswas, Abrar Tasneem Abir, Wajdi Zaghouani
  
• TurQUaz at CheckThat! 2024: A Hybrid Approach of Fine-Tuning and In-Context Learning for Check-Worthiness Estimation369-377
  Mehmet Eren Bulut, Kaan Efe Keleş, Mucahid Kutlu
  
• HYBRINFOX at CheckThat! 2024 - Task 2: Enriching BERT Models with the Expert System VAGO for Subjectivity Detection378-386
  Morgane Casanova, Julien Chanson, Benjamin Icard, Géraud Faye, Guillaume Gadek, Guillaume Gravier, Paul Égré
  
• Fired_from_NLP at CheckThat! 2024: Estimating the Check-Worthiness of Tweets Using a Fine-tuned Transformer-based Approach387-395
  Md. Sajid Alam Chowdhury, Anik Mahmud Shanto, Mostak Mahmud Chowdhury, Hasan Murad, Udoy Das
  
• TurQUaz at CheckThat! 2024: Creating Adversarial Examples using Genetic Algorithm396-404
  Basak Demirok, Selin Mergen, Bugra Oz, Mucahid Kutlu
  
• Mirela at CheckThat! 2024: Check-worthiness of Tweets with Multilingual Embeddings and Adversarial Training405-410
  Mirela Dryankova, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov
  
• HYBRINFOX at CheckThat! 2024 - Task 1: Enhancing Language Models with Structured Information for Check-Worthiness Estimation411-418
  Géraud Faye, Morgane Casanova, Benjamin Icard, Julien Chanson, Guillaume Gadek, Guillaume Gravier, Paul Egré
  
• Eevvgg at CheckThat! 2024: Evaluative Terms, Pronouns and Modal Verbs as Markers of Subjectivity in Text419-425
  Ewelina Gajewska
  
• UniBO at CheckThat! 2024: Multi-lingual and Multi-label Persuasion Technique Detection in News with Data Augmentation and Sequence-Token Classifiers426-434
  Paolo Gajo, Luca Giordano, Alberto Barrón-Cedeño
  
• DSHacker at CheckThat! 2024: LLMs and BERT for Check-Worthy Claims Detection with Propaganda Co-occurrence Analysis435-445
  Paweł Golik, Arkadiusz Modzelewski, Aleksander Jochym
  
• CLaC-2 at CheckThat! 2024: A Zero-Shot Model for Check-Worthiness and Subjectivity Classification446-452
  Shayne Gruman, Leila Kosseim
  
• TextTrojaners at CheckThat! 2024: Robustness of Credibility Assessment with Adversarial Examples through BeamAttack453-472
  David Guzman Piedrahita, Arnisa Fazla, Lucas Krauter
  
• Palöri at CheckThat! 2024 Shared Task 6: GloTa - Combining GloVe Embeddings with RoBERTa for Adversarial Attack473-482
  Haokun He, Yafeng Song, Dylan Massey
  
• SSN-NLP at CheckThat! 2024: Assessing the Check-Worthiness of Tweets and Debate Excerpts Using Traditional Machine Learning and Transformer Models483-488
  Sanjai Balajee Kannan Giridharan, Sanjjit Sounderrajan, B Bharathi, Nilu R. Salim
  
• AuthEv-LKolb at CheckThat! 2024: A Two-Stage Approach To Evidence-Based Social Media Claim Verification489-505
  Luis Kolb, Allan Hanbury
  
• OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text Generation506-519
  Włodzimierz Lewoniewski, Piotr Stolarski, Milena Stróżyna, Elżbieta Lewańska, Aleksandra Wojewoda, Ewelina Księżniak, Marcin Sawiński
  
• FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruning520-537
  Yufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga
  
• Trio Titans at Check That! 2024 : Check Worthiness Estimation538-545
  Sai Geetha M, Prarthna M, Chiranjeev Prasannaa V V, Saritha M
  
• Mela at CheckThat! 2024: Transferring Persuasion Detection from English to Arabic - A Multilingual BERT Approach546-551
  Sara Nabhani, Md Abdur Razzaq Riyadh
  
• SemanticCuetSync at CheckThat! 2024: Finding Subjectivity in News Articles using Llama552-559
  Ashraful Islam Paran, Md. Sajjad Hossain, Symom Hossain Shohan, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque
  
• SEUPD@CLEF: Team Axolotl on Rumor Verification using Evidence from Authorities560-569
  Andrea Pasin, Nicola Ferro
  
• SSN-NLP at CheckThat! 2024: From Feature-based Algorithms to Transformers: A Study on Detecting Subjectivity570-579
  Pooja Premnath, Pranav Vaithiya Subramani, Nilu R Salim, Bharathi B
  
• MMU NLP at CheckThat! 2024: Homoglyphs are Adversarial Attacks580-589
  Charlie Roadhouse, Matthew Shardlow, Ashley Williams
  
• Tonirodriguez at CheckThat!2024: Is it Possible to Use Zero-Shot Cross-Lingual Methods for Subjectivity Detection in Low-Resources Languages?590-597
  Antonio Rodríguez, Elisabet Golobardes, Jaume Suau
  
• JK_PCIC_UNAM at CheckThat! 2024: Analysis of Subjectivity in News Sentences Using Transformers-Based Models598-604
  Karla Salas-Jimenez, Iván Díaz, Helena Gómez-Adorno, Gemma Bel-Enguix, Gerardo Sierra
  
• Indigo at CheckThat! 2024: Using Setfit: A Resource Efficient Technique for Subjectivity Detection in News Article.605-612
  Soumyadeep Sar, Dwaipayan Roy
  
• OpenFact at CheckThat! 2024: Cross-Lingual Transfer Learning for Check-Worthiness Detection613-631
  Marcin Sawinski, Krzysztof Węcel, Ewelina Księżniak
  
• SemanticCuetSync at CheckThat! 2024: Pre-trained Transformer-based Approach to Detect Check-Worthy Tweet632-640
  Symom Hossain Shohan, Md. Sajjad Hossain, Ashraful Islam Paran, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque
  
• DataBees at CheckThat! 2024: Check-Worthiness Estimation641-650
  Tanisha Sriram, Yadushree Venkatesh, Sowmya Anand, Bharathi B
  
• SINAI at CheckThat! 2024: Transformer-based Approaches for Check-Worthiness Classification651-657
  Sergiu Stoia, Jaime Collado-Montañez, Cristian Ibáñez-Bautista, Arturo Montejo-Ráez, María Teresa Martín-Valdivia, Manuel Carlos Díaz-Galiano
  
• SINAI at CheckThat! 2024: Stealthy Character-Level Adversarial Attacks Using Homoglyphs and Iterative Search658-665
  José Valle-Aguilera, Alberto J. Gutiérrez-Megías, Salud María Jiménez-Zafra, L. Alfonso Ureña-López, Eugenio Martínez-Cámara
  
• Fraunhofer SIT at CheckThat! 2024: Adapter Fusion for Check-Worthiness Detection666-671
  Inna Vogel, Pauline Möhle
  
• FC_RUG at CheckThat! 2024: Few-shot Learning Using GEITje for Check-Worthiness Detection in Dutch672-679
  Sanne Weering, Tommaso Caselli
  
• Checker Hacker at CheckThat! 2024: Detecting Check-Worthy Claims and Analyzing Subjectivity with Transformers680-686
  Syeda Duae Zehra, Kushal Chandani, Muhammad Khubaib, Ahmed Ali Aun Muhammed, Faisal Alvi, Abdul Samad
  

ELOQUENT: Evaluating Generative Language Models

• ELOQUENT 2024 — Topical Quiz Task687-690
  Jussi Karlgren, Aarne Talman
  
• Overview of the CLEF-2024 Eloquent Lab: Task 2 on HalluciGen691-702
  Luise Dürlich, Evangelia Gogoulou, Liane Guillou, Joakim Nivre, Shorouq Zahra
  
• ELOQUENT 2024 — Robustness Task703-707
  Magnus Sahlgren, Jussi Karlgren, Luise Dürlich, Evangelia Gogoulou, Aarne Talman, Shorouq Zahra
  
• Evaluating Poro-34B-Chat and Mistral-7B-Instruct-v0.1: LLM System Description for ELOQUENT at CLEF 2024708-711
  Vasumathi Neralla, Sander Bijl de Vroe
  
• GPT Hallucination Detection Through Prompt Engineering712-721
  Marco Siino, Ilenia Tinnirello
  
• Experimental Report on Robustness Task - ELOQUENT Lab @ CLEF 2024722-726
  Annika Simonsen
  
• The Two Sides of the Coin: Hallucination Generation and Detection with LLMs as Evaluators for LLMs727-758
  Anh Thu Bui, Saskia Felizitas Brech, Natalie Hußfeldt, Tobias Jennert, Melanie Ullrich, Timo Breuer, Narjes Nikzad Khasmakhi, Philipp Schaer
  

eRisk 2024: Early Risk Prediction on the Internet

• Overview of eRisk 2024: Early Risk Prediction on the Internet (Extended Overview)759-781
  Javier Parapar, Patricia Martin-Rodilla, David E. Losada, Fabio Crestani
  
• NUS-IDS@eRisk2024: Ranking Sentences for Depression Symptoms using Early Maladaptive Schemas and Ensembles782-793
  Beng Heng Ang, Sujatha Das Gollapalli, See-Kiong Ng
  
• REBECCA at eRisk 2024: Search for Symptoms of Depression Using Sentence Embeddings and Prompt-Based Filtering794-802
  Anna Barachanou, Filareti Tsalakanidou, Symeon Papadopoulos
  
• ELiRF-VRAIN at eRisk 2024: Using LongFormers for Early Detection of Signs of Anorexia803-812
  Andreu Casamayor, Vicent Ahuir, Antonio Molina, Lluís-Felip Hurtado
  
• NLP-UNED at eRisk 2024: Approximate Nearest Neighbors with Encoding Refinement for Early Detecting Signs of Anorexia813-824
  Hermenegildo Fabregat, Daniel Deniz, Andres Duque, Lourdes Araujo, Juan Martinez-Romo
  
• DS@GT eRisk 2024: Sentence Transformers for Social Media Risk Assessment825-833
  David Guecha, Aaryan Potdar, Anthony Miyaguchi
  
• MindwaveML at eRisk 2024: Identifying Depression Symptoms in Reddit Users834-840
  Raluca-Maria Hanciu
  
• Automatically Finding Evidence and Predicting Answers in Mental Health Self-Report Questionnaires841-850
  Diego Maupomé, Yves Ferstler, Sébastien Mosser, Marie-Jean Meurs
  
• SINAI at eRisk@ CLEF 2024: Approaching the Search for Symptoms of Depression and Early Detection of Anorexia Signs using Natural Language Processing.851-861
  Alba María Mármol-Romero, Adrián Moreno-Muñoz, Pablo Álvarez-Ojeda, Karla María Valencia-Segura, Eugenio Martínez-Cámara, Manuel García-Vega, Arturo Montejo-Ráez
  
• UMUTeam at eRisk@CLEF 2024: Fine-Tuning Transformer Models with Sentiment Features for Early Detection and Severity Measurement of Eating Disorders862-870
  Ronghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-Garcia
  
• APB-UC3M at eRisk 2024: Natural Language Processing and Deep Learning for the Early Detection of Mental Disorders871-880
  Alejandro Pardo Bascuñana, Isabel Segura Bedmar
  
• Measuring the severity of the signs of Eating Disorders using Machine Learning Techniques881-887
  Sachin Prasanna, Abhayjit Singh Gulati, Subhojit Karmakar, M Yoga Hiranmayi, Anand Kumar Madasamy
  
• Combining Recommender Systems and Language Models in Early Detection of Signs of Anorexia888-893
  Oskar Riewe-Perła, Agata Filipowska
  
• A Natural Language Processing Based Framework for Early Detection of Anorexia via Sequential Text Processing894-901
  Prateek Sarangi, Sumit Kumar, Shraddha Agarwal, Tanmay Basu
  
• A Time-Aware Approach to Early Detection of Anorexia: UNSL at eRisk 2024902-907
  Horacio Thompson, Marcelo Errecalde
  

EXIST: sEXism Identification in Social neTworks

• Overview of EXIST 2024 - Learning with Disagreement for Sexism Identification and Characterization in Tweets and Memes (Extended Overview)908-941
  Laura Plaza, Jorge Carrillo-De-Albornoz, Victor Ruiz, Alba Maeso, Berta Chulvi, Paolo Rosso, Enrique Amigó, Julio Gonzalo, Roser Morante, Damiano Spina
  
• RoBEXedda: Sexism Detection in Tweets942-957
  Giacomo Aru, Nicola Emmolo, Simone Marzeddu, Andrea Piras, Jacopo Raffi, Lucia C. Passaro
  
• Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot Learning958-965
  Amirmohammad Azadi, Baktash Ansari, Sina Zamani, Sauleh Eetemadi
  
• Penta ML at EXIST 2024: Tagging Sexism in Online Multimodal Content With Attention-enhanced Modal Context966-977
  Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Fabiha Haider, Fariha Tanjim Shifat, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan
  
• I2C-UHU at EXIST 2024: Transformer-Based Detection of Sexism and Source Intention in Memes Using a Learning with Disagreement Approach978-992
  Álvaro Carrillo-Casado, Javier Román-Pásaro, Jacinto Mata-Vázquez, Victoria Pachón-Álvarez
  
• FraunhoferSIT@EXIST2024: Leveraging Stacking Ensemble Learning for Sexism Detection993-1002
  Shiying Fan, Raphael Antonius Frick, Martin Steinebach
  
• NYCU-NLP at EXIST 2024: Leveraging Transformers with Diverse Annotations for Sexism Identification in Social Networks1003-1011
  Yi-Zeng Fang, Lung-Hao Lee, Juinn-Dar Huang
  
• LightGBM for Sexism Identification in Memes1012-1017
  Arnau García i Cucó, Miquel Obrador Reina
  
• Automatic Classification of Gender Stereotypes in Social Media Post1018-1025
  Shimi Gersome, Jerin Mahibha, Durairaj Thenmozhi
  
• I2C-UHU at EXIST2024: Learning from Divergence and Perspectivism for Sexism Identification and Source Intent Classification1026-1042
  Manuel Guerrero-García, Manuel Cerrejón-Naranjo, Jacinto Mata-Vázquez, Victoria Pachón-Álvarez
  
• Enhancing Sexism Detection in Tweets with Annotator-Integrated Ensemble Methods and Multimodal Embeddings for Memes1043-1057
  Martha Paola Jimenez-Martinez, Joan Manuel Raygoza-Romero, Carlos Eduardo Sánchez-Torres, Irvin Hussein Lopez-Nava, Manuel Montes-Y-Gómez
  
• Sexism Identification in Social Networks using TF-IDF Embeddings, PreProccessing, Feature Selection, Word/Char N-Grams and Various Machine Learning Models In Spanish and English1058-1069
  Ron Keinan
  
• Multilingual Sexism Identification via Fusion of Large Language Models1070-1079
  Sahrish Khan, Gabriele Pergola, Arshad Jhumka
  
• RoJiNG-CL at EXIST 2024: Leveraging Large Language Models for Multimodal Sexism Detection in Memes1080-1090
  Jing Ma, Rong Li
  
• A Contrastive Learning Based Approach to Detect Sexism in Memes1091-1097
  Fariha Maqbool, Elisabetta Fersini
  
• Sexism Identification in Social Networks: Advances in Automated Detection - A Report on the Exist Task at CLEF1098-1106
  Nimra Maqbool
  
• VerbaNex AI at CLEF EXIST 2024: Detection of Online Sexism using Transformer Models and Profiling Techniques1107-1113
  Elizabeth Martinez, Juan Cuadrado, Juan Carlos Martinez Santos, Edwin Puertas
  
• DiTana-PV at sEXism Identification in Social neTworks (EXIST) tasks 4 and 6: The Effect of Translation in Sexism Identification1114-1121
  Aitana Menárguez-Box, Diego Torres-Bertomeu
  
• NICA at EXIST CLEF Tasks 20241122-1134
  Aylin Naebzadeh, Melika Nobakhtian, Sauleh Eetemadi
  
• UMUTeam at EXIST 2024: Multi-modal Identification and Categorization of Sexism by Feature Integration1135-1147
  Ronghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-Garcia
  
• Multilingual Sexism Detection in Memes, A CLIP-Enhanced Machine Learning Approach1148-1156
  Umera Wajeed Pasha
  
• Language-based Mixture of Transformers for EXIST20241157-1164
  Alexandru Petrescu, Ciprian-Octavian Truică, Elena-Simona Apostol
  
• Sexism Identification in Social Networks with Generation-based Language Models1165-1176
  Le Minh Quan, Dang Van Thin
  
• PINK at EXIST2024: A Cross-Lingual and Multi-Modal Transformer Approach for Sexism Detection in Memes1177-1186
  Giulia Rizzi, David Gimeno-Gómez, Elisabetta Fersini, Carlos-D. Martínez-Hinarejos
  
• Concatenated Transformer Models Based On Levels Of Agreements For Sexism Detection1187-1197
  Victor Ruiz, Jorge Carrillo-de-Albornoz, Laura Plaza
  
• Team Aditya at EXIST 2024 – Detecting Sexism in Multilingual Tweets using Contrastive Learning Approach1198-1202
  Aditya Shah, Aditya Gokhale
  
• The Wisdom of Weighing: Stacking Ensembles for a More Balanced Sexism Detector1203-1213
  Abhay Shanbhag, Suramya Jadhav, Atharva Date, Sumedh Joshi, Sheetal Sonawane
  
• Penta-nlp at EXIST 2024 Task 1-3: Sexism Identification, Source Intention, Sexism Categorization In Tweets1214-1227
  Fariha Tanjim Shifat, Fabiha Haider, Md Sakib Ul Rahman Sourove, Deeparghya Dutta Barua, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan
  
• Prompt Engineering for Identifying Sexism using GPT Mistral 7B1228-1236
  Marco Siino, Ilenia Tinnirello
  
• RMIT-IR at EXIST Lab at CLEF 20241237-1252
  Tony Smith, H Ruda Nie, Johanne R. Trippas, Damiano Spina
  
• Sexism Identification in Tweets Using Machine Learning Approaches1253-1259
  Murari Sreekumar, Shreyas Karthik, Durairaj Thenmozhi, Shriram Gopalakrishnan, Krithika Swaminathan
  
• Better Together: LLM and Neural Classification Transformers to Detect Sexism1260-1273
  Judith Tavarez-Rodríguez, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy
  
• Sexism Identification in Tweets using BERT and XLM - Roberta1274-1279
  Maha Usmani, Rania Siddiqui, Samin Rizwan, Faryal Khan, Faisal Alvi, Abdul Samad
  
• Cracking Down on Digital Misogyny with MULTILATE a MULTImodaL hATE Detection System1280-1296
  Advaitha Vetagiri, Prateek Mogha, Partha Pakray
  
• Stacked Reflective Reasoning in Large Neural Language Models1297-1311
  Kapioma Villarreal Haro, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy
  

iDPP: Intelligent Disease Progression Prediction

• Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge1312-1331
  Giovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel Garcia Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro
  
• ALSFRS-R Score Prediction for Amyotrophic Lateral Sclerosis1332-1340
  Guido Barducci, Flavio Sartori, Giovanni Birolo, Tiziana Sanavia, Piero Fariselli
  
• Predicting Multiple Sclerosis Relapses Using Patient Exposure Trajectories1341-1352
  Pietro Bosoni, Mahin Vazifehdan, Daniele Pala, Eleonora Tavazzi, Roberto Bergamaschi, Riccardo Bellazzi, Arianna Dagliati
  
• Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative Study1353-1365
  Elena Marinello, Alessandro Guazzo, Enrico Longato, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo
  
• Predicting the Functional Rating Scale and Self-Assessment Status of ALS Patients with Sensor Data1366-1379
  Andreia S. Martins, Daniela M. Amaral, Eduardo N. Castanho, Diogo F. Soares, Ruben Branco, Sara C. Madeira, Helena Aidos
  
• Machine Learning for ALSFRS-R Score Prediction: Making Sense of the Sensor Data1380-1391
  Ritesh Mehta, Aleksandar Pramov, Shashank Verma
  
• UBCS at IDPP: Predicting Patient Self-Assessment Score from Sensor Data using Machine Learning Algorithms1392-1400
  Chibuzor Chukwuemeka Okere, Edwin Thuma, Gontlafetse Mosweunyane
  
• BIT.UA at iDPP: Predictive Analytics on ALS Disease Progression Using Sensor Data with Machine Learning1401-1411
  Jorge Miguel Silva, José Luis Oliveira
  

ImageCLEF: Multimodal Challenge in CLEF

• Overview of the 2024 ImageCLEFmedical GANs Task - Investigating Generative Models' Impact on Biomedical Synthetic Images1412-1428
  Alexandra-Georgiana Andrei, Ahmedkhan Radzhabov, Dzmitry Karpenka, Yuri Prokopchuk, Vassili Kovalev, Bogdan Ionescu, Henning Müller
  
• Overview of ImageCLEFmedical 2024 – Medical Visual Question Answering for Gastrointestinal Tract1429-1436
  Steven Hicks, Andrea Storås, Pål Halvorsen, Michael Riegler, Vajira Thambawita
  
• Overview of ImageCLEFmedical 2024 – Caption Prediction and Concept Detection1437-1455
  Johannes Rückert, Asma Ben Abacha, Alba G. Seco de Herrera, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir, Henning Schäfer, Benjamin Bracke, Hendrik Damm, Tabea M. G. Pakull, Cynthia Sabrina Schmidt, Henning Müller, Christoph M. Friedrich
  
• Overview of the MEDIQA-MAGIC Task at ImageCLEF 2024: Multimodal And Generative TelemedICine in Dermatology1456-1462
  Wen-Wai Yim, Asma Ben Abacha, Yujuan Fu, Zhaoyi Sun, Meliha Yetisgen, Fei Xia
  
• IRLab@IIT_BHU at MEDIQA-MAGIC 2024: Medical Question Answering using Classification model1463-1473
  Arvind Agrawal, Sukomal Pal
  
• SSN-MLRG at Text to Picto 2024 : A BERT-Based Approach for Mapping French Sentences to Pictogram Terms1474-1479
  Bhavana Anand, Themozhi J, Shreyas Sai R, Charumathi P, Mirnalinee Tt
  
• AI Multimedia Lab at ImageCLEFmedical GANs 2024: Deep Learning Approaches for Analyzing Synthetic Medical Images1480-1489
  Alexandra-Georgiana Andrei, Mihai Gabriel Constantin, Mihai Dogariu, Bogdan Ionescu
  
• Medical Image Captioning using CUI-based Classification and Feature Similarity1490-1499
  Masaki Aono, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura
  
• KDE-med-lab at ImageCLEF 2024: Identify data and detect generative models using CNN by lung segmentation based on U-net1500-1507
  Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono
  
• Concept Detection and Caption Prediction of Radiology Images Using Convolutional Neural Networks1508-1516
  Prabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km
  
• Evaluation of the Privacy of Images Generated by ImageCLEFmedical GANs 2024 Based on Similarity Methods1517-1524
  Shitong Cao, Xiaobing Zhou
  
• VisualT5: Multitasking Caption and Concept Prediction with Pre-trained ViT, T5 and Customized Spatial Attention in Radiological Images1525-1532
  Diedre Carmo, Letícia Rittner, Roberto Lotufo
  
• MMCP Team at ImageCLEFmed MEDVQA-GI 2024 Task: Diffusion Models for Text-to-Image Generation of Colonoscopy Images1533-1544
  Mikhail Chaichuk, Elena Tutubalina
  
• VisionQAries at MEDIQA-MAGIC 2024: Small Vision Language Models for Dermatological Diagnosis1545-1551
  Patrycja Cieplicka, Julia Kłos, Maciej Morawski
  
• SSNMLRGKSR at ImageCLEFmedical Caption 2024: Medical Concept Detection using DenseNet-121 with MultiLabelBinarizer1552-1559
  Ramyaa Dhinagaran, Sheerin Sitara Noor Mohamed, Kavitha Srinivasan
  
• Advancing AI-Powered Medical Image Synthesis: Insights from MedVQA-GI Challenge Using CLIP, Fine-Tuned Stable Diffusion, and Dream-Booth + LoRA1560-1578
  Ojonugwa Oluwafemi Ejiga Peter, Md Mahmudur Rahman, Fahmi Khalifa
  
• Text-To-Picto using Lexical Simplification1579-1584
  Abbhinav Elliah, Ananth Narayanan P, Bhuvan S, P Mirunalini
  
• Fingerprint Identification of Generative Models Using a MultiFormer Ensemble Approach1585-1598
  Md. Ismail Siddiqi Emon, Mahmudul Hoque, Md Rakibul Hasan, Fahmi Khalifa, Md Mahmudur Rahman
  
• YuanAI at MEDIQA-MAGIC 2024: Improving Medical VQA Performance through Parameter-Efficient Fine-Tuning1599-1607
  Hsian-Hong Fu, Hsien-Cheng Huang
  
• KDE Lab at ImageCLEFmedical GANs 20241608-1612
  Shota Fukuyama, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono
  
• Detecting Training Data and Generative Model Fingerprints in Synthetic CT Scans Using Machine Learning1613-1618
  Amilcare Gentili
  
• Medical Image Interpretation with Large Multimodal Models1619-1639
  Mahmudul Hoque, Md Rakibul Hasan, Md. Ismail Siddiqi Emon, Fahmi Khalifa, Md Mahmudur Rahman
  
• Identifying Training Data "Fingerprints" Using Border Enhancing Image Processing Methods and Their Ensemble1640-1644
  Koki Inoue, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono
  
• Predicting Captions and Detecting Concepts for Medical Images: Contributions of the DBS-HHU Team to ImageCLEFmedical Caption 20241645-1655
  Heiko Kauschke, Kirill Bogomasov, Stefan Conrad
  
• A Transformer Based Approach for Text-to-Picto Generation1656-1661
  Avaneesh Koushik, Jithu Morrison S, P Mirunalini, Jothir Aditya R K
  
• Analyzing Generated Images using Machine Learning1662-1667
  Diana Miranda, Aparna Rane, Bipin Naik
  
• Automatic Medical Concept Detection on Images: Dividing the Task into Smaller Ones1668-1680
  Axel Moncloa-Muro, Graciela Ramirez-Alonso, Fernando Martinez-Reyes
  
• DS@BioMed at ImageCLEFmedical Caption 2024: Enhanced Attention Mechanisms in Medical Caption Generation through Concept Detection Integration1681-1694
  Nhi Ngoc-Yen Nguyen, Huy Le Tu, Phuong Dieu Nguyen, Tan Nhat Do, Triet Minh Thai, Thien B. Nguyen-Tat
  
• UIT-DarkCow team at ImageCLEFmedical Caption 2024: Diagnostic Captioning for Radiology Images Efficiency with Transformer Models1695-1710
  Quan Van Nguyen, Huy Quang Pham, Dan Quang Tran, Thang Kien-Bao Nguyen, Nhat-Hao Nguyen-Dang, Thien B. Nguyen-Tat
  
• UIT-2Q2T at ImageCLEFmedical 2024 Caption: Multimodal medical image captioning using Bootstrapping Language-Image Pre-training1711-1719
  Thien V. Phan, Trinh K. Nguyen, Quang A. D. D. Hoang, Quan T. Phan, Thien B. Nguyen-Tat
  
• Leveraging Diverse CNN Architectures for Medical Image Captioning: DenseNet-121, MobileNetV2, and ResNet-50 in ImageCLEF 20241720-1728
  Sriram Ram, Shashaank Vinoth, Rahul Natesh Gopalakrishnan, Aastick Amirteswar Balakumar, Lekshmi Kalinathan, Thomas Abraham Joseph Velankanni
  
• AUEB NLP Group at ImageCLEFmedical Caption 20241729-1745
  Marina Samprovalaki, Anna Chatzipapadopoulou, Georgios Moschovis, Foivos Charalampakos, Panagiotis Kaliosis, John Pavlopoulos, Ion Androutsopoulos
  
• Classification of Real and Generated Images Based on Feature Similarity1746-1754
  Huihui Tang, Hancheng Wang, Jining Chen
  
• GAN-Amis: Evaluating Clustering of GAN-Generated Medical Images Using Custom and Pre-trained CNN Architectures to Identify GAN Fingerprints1755-1762
  Aman Upganlawar, Aarti Lad, Arnav Desai
  
• PCLmed: Champion Solution for ImageCLEFmedical 2024 Caption Prediction Challenge via Medical Vision-Language Foundation Models1763-1774
  Bang Yang, Yue Yu, Yuexian Zou, Tong Zhang
  

JOKER Lab: Automatic Humour Analysis

• Overview of the CLEF 2024 JOKER Task 1: Humour-aware Information Retrieval1775-1785
  Liana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt
  
• Overview of the CLEF 2024 JOKER Task 2: Humour Classification According to Genre and Technique1786-1799
  Victor Manuel Palma Preciado, Grigori Sidorov, Liana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt
  
• Overview of the CLEF 2024 JOKER Task 3: Translate puns from English to French1800-1810
  Liana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt
  
• JOKER Track @ CLEF 2024: the Jokesters' approaches for retrieving, classifying, and translating wordplay1811-1817
  Harouna Baguian, Huynh Nina Ashley
  
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 JOKER Track: From ‘LOL’ to ‘MDR’ Using Artificial Intelligence Models to Retrieve and Translate Puns1818-1825
  Antonia Bartulović, Dóra Paula Váradi
  
• PunDerstand @ CLEF JOKER 2024: Who’s Laughing Now? Humor Classification by Genre & Technique1826-1833
  Ryan Rony Dsilva, Nidhi Bhardwaj
  
• Working Notes of CLEF 2024: Effective Humor Analysis and Translation1834-1840
  Regina Elagina, Petra Vučić
  
• ORPAILLEUR & SyNaLP at CLEF 2024 Task 2: Good Old Cross Validation for Large Language Models Yields the Best Humorous Detection1841-1856
  Pierre Epron, Gaël Guibon, Miguel Couceiro
  
• CLEF 2024 Joker Task 1: Exploring Pun Detection Using The T5 Transformer Model1857-1861
  Arina Gepalova, Adrian-Gabriel Chifu, Sébastien Fournier
  
• Thinking, Fast and Slow: From the Speed of FastText to the Depth of Retrieval Augmented Large Language Models For Humour Classification1862-1867
  Jana Viktória Kováčiková, Marek Šuppa
  
• CLEF 2024 JOKER Tasks 1-3: Humour identification and classification1868-1875
  Rowan Mann, Tomislav Mikulandric
  
• CLEF 2024 JOKER Task 2 : Using RoBERTa and Bert-uncased for Humour Classification According to Genre and Technique1876-1879
  Sarvesh Narayanan, Jayasimman J, Shiva Ganesh V
  
• NLPalma Joker 2024: Yet, no Humor with Humorousness - Task 2 Humour Classification According to Genre and Technique1880-1888
  Victor Manuel Palma-Preciado, Carolina Palma-Preciado, Grigori Sidorov
  
• Comparative Evaluation of Humour Translation from English to Spanish: A Study with BLOOM and Googletrans1889-1894
  Olga Popova
  
• Vayam Solve Kurmaha @ CLEF 2024: Task 2: Humor Classification according to Genre and Technique using BERT Embeddings and Transformers1895-1901
  Dhannya S M, Lakshmi Priya S, Shreedevi Seluka Balaji, Sai Nikitha N.S.R, Shwetha S, Surabhi Kamath, Srinidhi Lakshmi Narayanan
  
• CLEF 2024 JOKER Task 2: Using BERT and Random Forest Classifier for Humor Classification According to Genre and Technique1902-1908
  M Saipranav, Jaswanth Sridharan, Gautham Narayan G, Angel Deborah S, Rajalakshmi S, Mirnalinee T T, Samyuktaa Sivakumar
  
• University of Amsterdam at the CLEF 2024 Joker Track1909-1922
  Emma Schuurman, Mick Cazemier, Luc Buijs, Jaap Kamps
  
• Team Humour Insights at JOKER 2024 Task 2: Humour Classification According To Genre And Technique1923-1932
  Rakshith Subramanian, Vaishnavi S, B Bharathi
  
• Humour Classification by Fine-tuning LLMs: CYUT at CLEF 2024 JOKER Lab Subtask Humour Classification According to Genre and Technique1933-1947
  Shih-Hung Wu, Yu-Feng Huang, Tsz-Yeung Lau
  

LifeCLEF: species identification and prediction

• Overview of BirdCLEF 2024: Acoustic identification of under-studied bird species in the Western Ghats1948-1957
  Stefan Kahl, Tom Denton, Holger Klinck, Vijay Ramesh, Viral Joshi, Meghana Srivathsa, Akshay Anand, Chiti Arvind, Harikrishnan Cp, Suyash Sawant, Robin Vv, Hervé Glotin, Hervé Goëau, Willem-Pier Vellinga, Robert Planqué, Alexi Joly
  
• Overview of FungiCLEF 2024: Revisiting Fungi Species Recognition Beyond 0-1 Cost1958-1965
  Lukas Picek, Milan Šulc, Jiří Matas
  
• Overview of GeoLifeCLEF 2024: Species Composition Prediction with High Spatial Resolution at Continental Scale using Remote Sensing1966-1977
  Lukas Picek, Christophe Botella, Maximilien Servajean, César Leblanc, Rémi Palard, Théo Larcher, Benjamin Deneu, Diego Marcos, Joaquim Estopinan, Pierre Bonnet, Alexis Joly
  
• Overview of PlantCLEF 2024: Multi-species Plant Identification in Vegetation Plot Images1978-1988
  Hervé Goëau, Vincent Espitalier, Pierre Bonnet, Alexis Joly
  
• Overview of SnakeCLEF 2024: Revisiting Snake Species Identification in Medically Important Scenarios1989-2000
  Lukas Picek, Marek Hrúz, Andrew M. Durso
  
• Combining Present-Only and Present-Absent Data with Pseudo-Label Generation for Species Distribution Modeling2001-2008
  Yi-Chia Chen, Tai Peng, Wei-Hua Li, Chu-Song Chen
  
• Multi-modal Feature Fusion Networks for GeoLifeCLEF 20242009-2015
  Zehua Cheng, Wei Dai, Jiahao Sun
  
• Fine-Grained Classification for Poisonous Fungi Identification with Transfer Learning2016-2026
  Christopher Chiu, Maximilian Heil, Teresa Kim, Anthony Miyaguchi
  
• Patch-wise Inference using Pre-trained Vision Transformers: NEUON Submission to PlantCLEF 20242027-2043
  Sophia Chulif, Hamza Ahmed Ishrat, Yang Loong Chang, Sue Han Lee
  
• Methods for Training Convolutional Neural Networks to Identify Bird Species in Complex Soundscape Recordings2044-2052
  Konstantin Dmitriev
  
• Generalizable Training Techniques for Fine-Grained Long-Tailed Image Recognition: Transferring Methods Optimized for FungiCLEF 2024 to SnakeCLEF 20242053-2065
  Jack N. Etheredge
  
• OpenWGAN-GP for Fine-Grained Open-Set Fungi Classification2066-2082
  Jack N. Etheredge
  
• Utilising DINOv2 for Domain Adaptation in Vegetation Plot Analysis2083-2092
  Stephen Foy, Simon McLoughlin
  
• Multi-Label Plant Species Classification with Self-Supervised Vision Transformers2093-2102
  Murilo Gustineli, Anthony Miyaguchi, Ian Stalter
  
• Domain Adaption for Birdcall Recognition: Progressive Knowledge Distillation with Semi-Supervised and Self-Supervised Soundscape Labeling2103-2109
  Lihang Hong
  
• Improving Bird Recognition using Pseudo-Labeled Recordings from the Target Location2110-2118
  Mario Lasseck
  
• Tighnari: Multi-modal Plant Species Prediction Based on Hierarchical Cross-Attention Using Graph-Based and Vision Backbone-Extracted Features2119-2143
  Haixu Liu, Penghao Jiang, Zerui Tao, Muyan Wan, Qiuzhuang Sun
  
• Tile Compression and Embeddings for Multi-Label Classification in GeoLifeCLEF 20242144-2157
  Anthony Miyaguchi, Patcharapong Aphiwetsa, Mark McDuffie
  
• Transfer Learning with Pseudo Multi-Label Birdcall Classification for DS@GT BirdCLEF 20242158-2169
  Anthony Miyaguchi, Adrian Cheung, Murilo Gustineli, Ashley Kim
  
• Transfer Learning with Self-Supervised Vision Transformers for Snake Identification2170-2177
  Anthony Miyaguchi, Murilo Gustineli, Austin Fischer, Ryan Lundqvist
  
• Bird-Species Audio Identification, Ensembling of EfficientNet-B0 and Pre-trained EfficientNet-B1 model2178-2187
  Aaditya Porwal
  
• Exploring Biodiversity: A Multi-Model Approach to Multi-Label Plant Species Prediction2188-2200
  Darren Rawlings, Tim Chopard
  
• TUC Media Computing at BirdCLEF 2024: Improving Birdsong Classification Through Single Learning Models2201-2208
  Arunodhayan Sampathkumar, Tobias Schlosser, Danny Kowerko
  
• Do Not Lose to Losses for SnakeCLEF20242209-2214
  Matěj Sieber, Tomáš Železný
  
• Multimodal networks for Species Distribution Modeling2215-2222
  Aman R. Syayfetdinov
  
• Say No to the Poisonous Fungi: An Effective Strategy for Reducing 0-1 Cost in FungiCLEF20242223-2233
  Bao-Feng Tan, Yang-Yang Li, Peng Wang, Lin Zhao, Xiu-Shen Wei
  
• Multibranch Co-training to Mine Venomous Feature Representation: A Solution to SnakeCLEF20242234-2243
  Peng Wang, Yangyang Li, Bao-Feng Tan, Yi-Chao Zhou, Yong Li, Xiu-Shen Wei
  
• Addressing the Challenges of Domain Shift in Bird Call Classification for BirdCLEF 20242244-2259
  Emiel Witting, Hugo de Heer, Jeffrey Lim, Cahit Tolga Kopar, Kristóf Sándor
  
• Poison-Aware Open-Set Fungi Classification: Reducing the Risk of Poisonous Confusion2260-2266
  Stefan Wolf, Philipp Thelen, Jürgen Beyerer
  

LongEval: Longitudinal Evaluation of Model Performance

• Extended Overview of the CLEF 2024 LongEval Lab on Longitudinal Evaluation of Model Performance2267-2289
  Rabab Alkhalifa, Hsuvas Borkakoty, Romain Deveaud, Alaa El-Ebshihy, Luis Espinosa-Anke, Tobias Fink, Petra Galuščáková, Gabriela González-Sáez, Lorraine Goeuriot, David Iommi, Maria Liakata, Harish Tayyar Madabushi, Pablo Medina-Alias, Philippe Mulhem, Florina Piroi, Martin Popel, Arkaitz Zubiaga
  
• SEUPD@CLEF: Team Kalu on improving Search Engine Performance with Query Expansion and Re-Ranking Approach2290-2303
  Kimia Abedini, Arwa Fahoud, Akan Akysh, Nicola Ferro
  
• Team OpenWebSearch at CLEF 2024: LongEval2304-2313
  Daria Alexander, Maik Fröbe, Gijs Hendriksen, Ferdinand Schlatt, Matthias Hagen, Djoerd Hiemstra, Martin Potthast, Arjen P. de Vries
  
• SEUPD@CLEF: Team DAM on Reranking Using Sentence Embedders2314-2335
  Alberto Basaglia, Andrea Stocco, Milica Popović, Nicola Ferro
  
• SEUPD@CLEF: Team MOUSE on Enhancing Search Engines Effectiveness with Large Language Models.2336-2355
  Lorenzo Cazzador, Francesco Luigi De Faveri, Filippo Franceschini, Lorenzo Pamio, Samuel Piron, Nicola Ferro
  
• SEUPD@CLEF: Team IRIS on Temporal Evolution of Query Expansion and Rank Fusion Techniques Applied to Cross-Encoder Re-Rankers.2356-2383
  Filippo Galli, Manuel Rigobello, Michela Schibuola, Riccardo Zuech, Nicola Ferro
  
• Team Galápagos Tortoise at LongEval 2024: Neural Re-Ranking and Rank Fusion for Temporal Stability2384-2395
  Marlene Gründel, Malte Weber, Johannes Franke, Jan Heinrich Merker
  
• Leveraging Prior Relevance Signals in Web Search2396-2406
  Jüri Keller, Timo Breuer, Philipp Schaer
  
• Analyzing the Effectiveness of Listwise Reranking with Positional Invariance on Temporal Generalizability2407-2423
  Soyoung Yoon, Jongyoon Kim, Seung-won Hwang
  

PAN: Lab on Stylometry and Digital Text Forensics

• Overview of the Multi-Author Writing Style Analysis Task at PAN 20242424-2431
  Eva Zangerle, Maximilian Mayerl, Martin Potthast, Benno Stein
  
• Overview of the Multilingual Text Detoxification Task at PAN 20242432-2461
  Daryna Dementieva, Daniil Moskovskiy, Nikolay Babakov, Abinew Ali Ayele, Naquee Rizwan, Florian Schneider, Xintong Wang, Seid Muhie Yimam, Dmitry Ustalov, Elisei Stakovskii, Alisa Smirnova, Ashraf Elnagar, Animesh Mukherjee, Alexander Panchenko
  
• Overview of the Oppositional Thinking Analysis PAN Task at CLEF 20242462-2485
  Damir Korenčić, Berta Chulvi, Xavier Bonet-Casals, Mariona Taulé, Paolo Rosso, Francisco Rangel
  
• Overview of the “Voight-Kampff” Generative AI Authorship Verification Task at PAN and ELOQUENT 20242486-2506
  Janek Bevendorff, Matti Wiegmann, Jussi Karlgren, Luise Dürlich, Evangelia Gogoulou, Aarne Talman, Efstathios Stamatatos, Martin Potthast, Benno Stein
  
• Team Deloitte at PAN: A Novel Approach for Generative AI Text Detection2507-2510
  Harika Abburi, Nirmala Pudota, Balaji Veeramani, Edward Bowen, Sanmitra Bhattacharya
  
• Detection of Conspiracy vs. Critical Narratives and Their Elements using NLP2511-2520
  Aish Albladi, Cheryl Seals
  
• Oppositional Thinking Analysis: Conspiracy Theories vs Critical Thinking Narratives2521-2526
  Prabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km
  
• Team ap-team at PAN: LLM Adapters for Various Datasets2527-2535
  Galina Boeva, German Gritsai, Andrey Grabovoy
  
• Enhancing Human-Machine Authorship Discrimination in Generative AI Verification Task with BERT and Augmented Data2536-2540
  Haojie Cao, Zhongyuan Han, Jingyan Ye, Biao Liu, Yong Han
  
• Integrating Dual BERT Models and Causal Language Models for Enhanced Detection of Machine-Generated Texts2541-2546
  Jitong Chen, Leilei Kong
  
• Team Chen at PAN: Integrating R-Drop and Pre-trained Language Model for Multi-author Writing Style Analysis2547-2553
  Zhaotian Chen, Yong Han, Yusheng Yi
  
• DSVS at PAN 2024: Ensemble Approach of Transformer-based Language Models for Analyzing Conspiracy Theories Against Critical Thinking Narratives2554-2565
  Sergio Damián, Brian Herrera, David Vázquez, Hiram Calvo, Edgardo Felipe-Riverón, Cornelio Yáñez-Márquez
  
• A Study on NLP Model Ensembles and Data Augmentation Techniques for Separating Critical Thinking from Conspiracy Theories in English Texts2566-2571
  Iñaki del Campo Sánchez-Hermosilla, Angel Panizo-Lledot, David Camacho
  
• Automatic Identification of Conspiracy Theories Using BERT2572-2575
  Daniel Yacob Espinosa, Grigori Sidorov, Eusebio Ricárdez-Vázquez
  
• Linguistic_Hygenist at PAN 2024 TextDetox: HybridDetox - A Combination of Supervised and Unsupervised Methods for Effective Multilingual Text Detoxification2576-2584
  Susmita Gangopadhyay, M.Taimoor Khan, Hajira Jabeen
  
• BLGAV：Generative AI Author Verification Model Based on BERT and BiLSTM2585-2592
  Linjiu Guo, Wenyin Yang, Li Ma, Jinli Ruan
  
• A Machine-Generated Text Detection Model Based on Text Multi-Feature Fusion2593-2602
  Mingcan Guo, Zhongyuan Han, Haoyang Chen, Jiangao Peng
  
• Detection of conspiracy-related messages in Telegram with anonymized named entities2603-2612
  Juan Gómez-Romero, Santiago González-Silot, Andrés Montoro-Montarroso, Miguel Molina-Solana, Eugenio Martínez Cámara
  
• An Oppositional Thinking Analysis Method Using BERT-based Model with BiGRU2613-2618
  Qingbiao Hu, Zhongyuan Han, Jiangao Peng, Mingcan Guo, Chang Liu
  
• Author Authentication of Generative AI Based on Bert by Regularization Method2619-2626
  Baijian Huang, Changle Zhong, Kai Yan, Yong Han
  
• Conspiracy Theory Text Classification Based on CT-BERT and BETO Models2627-2631
  Jiahong Huang, Zhongyuan Han, Ruihao Zhu, Mingcan Guo, Kaiyin Sun
  
• Generative AI Authorship Verification Of Tri-Sentence Analysis Base On The Bert Model2632-2637
  Jijie Huang, Yang Chen, Man Luo, Yonglan Li
  
• Generative AI Authorship Verification Based on Contrastive Learning and Domain Adaptation2638-2644
  Kaicheng Huang, Haoliang Qi, Kai Yan
  
• Authorial Language Models For AI Authorship Verification2645-2652
  Weihang Huang, Jack Grieve
  
• Team Text Understanding and Analysis at PAN: Utilizing BERT Series Pre-training Model for Multi-Author Writing Style Analysis2653-2657
  Yingzhou Huang, Leilei Kong
  
• DeBERTa-v3 with R-Drop regularization for Multi-Author Writing Style Analysis2658-2664
  Zhijian Huang, Leilei Kong
  
• Small Language Models and Large Language Models in Oppositional thinking analysis: Capabilities, Biases and Challenges2665-2675
  Álvaro Huertas-García, Carlos Martí-González, Javier Muñoz, Enrique De Miguel Ambite
  
• Team karami-sh at PAN: Transformer-based Ensemble Learning for Multi-Author Writing Style Analysis2676-2681
  Mohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad
  
• Team karami-kheiri at PAN: Enhancing Machine-Generated Text Detection with Ensemble Learning Based on Transformer Models2682-2687
  Mohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad
  
• Team Gladiators at PAN: Improving Author Identification: A Comparative Analysis of Pre-Trained Transformers for Multi-Author Classification2688-2694
  Areeb Adnan Khan, Mohit Rai, Khuzaima Ali Khan, Syed Jahania Shah, Faisal Alvi, Abdul Samad
  
• Team OpenFact at PAN 2024: Fine-Tuning BERT Models with Stylometric Enhancements2695-2703
  Ewelina Księżniak, Krzysztof Węcel, Marcin Sawiński
  
• Generative AI Authorship Verification based on ChatGLM2704-2709
  Haotian Lei, Xiangyu Liu, Guo Niu, Yan Zhou, Yuexia Zhou
  
• Fine-Tuned Reasoning for Writing Style Analysis2710-2715
  Xiaofeng Liang, Fanzhi Zeng, Yan Zhou, Xiangyu Liu, Yuexia Zhou
  
• NYCU-NLP at PAN 2024: Integrating Transformers with Similarity Adjustments for Multi-Author Writing Style Analysis2716-2721
  Tzu-Mi Lin, Yu-Hsin Wu, Lung-Hao Lee
  
• Voight-Kampff Generative AI Authorship Verification Based on T52722-2727
  Zhaojian Lin, Fanzhi Zeng, Yan Zhou, Xiangyu Liu, Yuexia Zhou
  
• A Verifying Generative Text Authorship Model With Regularized Dropout2728-2734
  Zijie Lin, Zhongyuan Han, Leilei Kong, Miaoling Chen, Shuyi Zhang, Jiangao Peng, Kaiyin Sun
  
• Team nlpln at PAN 2024: An Approach to Classifying Conspiratorial and Critical Public Health Narratives With Zero-shot and Sequence Labeling2735-2743
  Biao Liu, Zhongyuan Han, Haojie Cao
  
• Team Liuc0757 at PAN: A Writing Style Embedding Method Based on Contrastive Learning for Multi-Author Writing Style Analysis2744-2749
  Chang Liu, Zhongyuan Han, Haoyang Chen, Qingbiao Hu
  
• Team foshan-university-of-guangdong at PAN: Adaptive Entropy-Based Stability-Plasticity for Multi-Author Writing Style Analysis2750-2754
  Xurong Liu, Hui Chen, Jiajun Lv
  
• AI Text Detection Method Based on Perplexity Features with Strided Sliding Window2755-2760
  Xurong Liu, Leilei Kong
  
• BaselineAvengers at PAN 2024: Often-Forgotten Baselines for LLM-Generated Text Detection2761-2768
  Ludwig Lorenz, Funda Zeynep Aygüler, Ferdinand Schlatt, Nailia Mirzakhmedova
  
• Multilingual Text Detoxification Using Google Cloud Translation and Post-Processing2769-2774
  Zhongyu Luo, Man Luo, Aiguo Wang
  
• Meta-Contrastive Learning for Generative AI Authorship Verification2775-2780
  Jiajun Lv, Yong Han, Leilei Kong
  
• Team fosu-stu at PAN: Supervised Fine-Tuning of Large Language Models for Multi Author Writing Style Analysis2781-2786
  Jiajun Lv, Yusheng Yi, Haoliang Qi
  
• Binary Battle: Leveraging Machine Learning and Transfer Learning Models to Distinguish between Conspiracy Theories and Critical Thinking2787-2796
  Sidharth Mahesh, Sonith Divakaran, Kavya Girish, Hosahalli Lakshmaiah Shashirekha
  
• IUCL at PAN 2024: Using Data Augmentation for Conspiracy Theory Detection2797-2806
  Shrirang Mhalgi, Srikar Kashyap Pulipaka, Sandra Kübler
  
• Team aida at PAN: Ensembling Normalized Log Probabilities2807-2813
  Pablo Miralles, Alejandro Martín, David Camacho
  
• Marsan at PAN 2024 TextDetox: ToxiCleanse RL, Paving the Way for Toxicity-Free Online Discourse2814-2823
  Maryam Najafi, Ehsan Tavan, Simon Colreavy
  
• AI Authorship Verification: An Ensembled Approach2824-2828
  Benjamin Ostrower, Jacob Wessell, Abhinav Bindal
  
• A Multilingual Text Detoxification Method Based on Few-shot Learning and CO-STAR Framework2829-2837
  Jiangao Peng, Zhongyuan Han, Huan Zhang, Jingyan Ye, Chang Liu, Biao Liu, Mingcan Guo, Haoyang Chen, Zijie Lin, Yujiao Tang
  
• RoBERTa and Bi-LSTM for Human vs AI Generated Text Detection2838-2842
  Panagiotis Petropoulos, Vasilis Petropoulos
  
• SomethingAwful at PAN 2024 TextDetox: Uncensored Llama 3 Helps to Censor Better2843-2851
  Sergey Pletenev
  
• PAN 2024 Multilingual TextDetox: Exploring Cross-lingual Transfer Using Large Language Models2852-2857
  Vitaly Protasov
  
• A Model Fusion Approach for Generative AI Authorship Verification2858-2865
  Rui Qin, Haoliang Qi, Yusheng Yi
  
• SmurfCat at PAN 2024 TextDetox: Alignment of Multilingual Transformers for Text Detoxification2866-2871
  Elisei Rykov, Konstantin Zaytsev, Ivan Anisimov, Alexandr Voronin
  
• Towards a Computational Framework for Distinguishing Critical and Conspiratorial Texts by Elaborating on the Context and Argumentation with LLMs2872-2880
  Ariana Sahitaj, Premtim Sahitaj, Salar Mohtaj, Sebastian Möller, Vera Schmitt
  
• Team riyahsanjesh at PAN: Multi-feature with CNN and Bi-LSTM Neural Network Approach to Style Change Detection2881-2885
  Riya Sanjesh, Alamelu Mangai
  
• BCAV: A Generative AI Author Verification Model Based on the Integration of Bert and CNN2886-2891
  Guihong Sun, Wenyin Yang, Li Ma
  
• PAN 2024 Multilingual TextDetox: Exploring Different Regimes For Synthetic Data Training For Multilingual Text Detoxification2892-2900
  Nikita Sushko
  
• MarSan at PAN: BinocularsLLM, Fusing Binoculars' Insight with the Proficiency of Large Language Models for Machine-Generated Text Detection2901-2912
  Ehsan Tavan, Maryam Najafi
  
• Conspiracy vs Critical Thinking Using an Ensemble of Transformers with Data Augmentation Techniques2913-2922
  Angelo Maximilian Tulbure, Mariona Coll Ardanuy
  
• Team iimasnlp at PAN: Leveraging Graph Neural Networks and Large Language Models for Generative AI Authorship Verification2923-2929
  Andric Valdez-Valenzuela, Helena Gómez-Adorno
  
• SINAI at PAN 2024 Oppositional Thinking Analysis: Exploring the Fine-Tuning Performance of Large Language Models2930-2940
  María Estrella Vallecillo-Rodríguez, María Teresa Martín-Valdivia, Arturo Montejo-Ráez
  
• SINAI at PAN 2024 TextDetox: Application of Chain of Thought with Self-Consistency Strategy in Large Language Models for Multilingual Text Detoxification2941-2950
  María Estrella Vallecillo-Rodríguez, Arturo Montejo-Ráez, María Teresa Martín-Valdivia
  
• Team baker at PAN: Enhancing Writing Style Change Detection with Virtual Softmax2951-2955
  Bingpei Wu, Yong Han, Kai Yan, Haoliang Qi
  
• Team lm-detector at PAN: Can NLI be an Appropriate Approach to Machine-Generated Text Detection2956-2962
  Guojun Wu, Qinghao Guan
  
• Team bingezzzleep at PAN: A Writing Style Change Analysis Model Based on RoBERTa Encoding and Contrastive Learning for Multi-Author Writing Style Analysis2963-2968
  Qida Wu, Leilei Kong, Zhanhong Ye
  
• BertT: A Hybrid Neural Network Model for Generative AI Authorship Verification2969-2975
  Zepeng Wu, Wenyin Yang, Li Ma, Zikai Zhao
  
• Team cnlp-nits-pp at PAN: Leveraging BERT for Accurate Authorship Verification: A Novel Approach to Textual Attribution2976-2987
  Annepaka Yadagiri, Dimpal Kalita, Abhishek Ranjan, Ashish Kumar Bostan, Parthib Toppo, Partha Pakray
  
• Continual Transfer Learning with Progress Prompt for Multi-Author Writing Style Analysis2988-2994
  Zhanhong Ye, Yutong Zhong, Chen Huang, Leilei Kong
  
• Token Prediction as Implicit Classification for Generative AI Authorship Verification2995-3001
  Zhanhong Ye, Yutong Zhong, Zhen Huang, Leilei Kong
  
• A Conspiracy Theory Text Detection Method based on RoBERTa and XLM-RoBERTa Models3002-3006
  Zhengqiao Zeng, Zhongyuan Han, Jingyan Ye, Yaozu Tan, Haojie Cao, Zengyao Li, Runjin Huang
  
• AI Authorship Verification Based On Deberta Model3007-3011
  Ye Zhu, Leilei Kong
  
• Conspiracy Theory Detection using Transformers with Multi-task and Multilingual Approaches3012-3020
  Leon Zrnić
  
• RAG Meets Detox: Enhancing Text Detoxification Using Open Large Language Models with Retrieval Augmented Generation3021-3031
  Erik Řehulka, Marek Šuppa
  

qCLEF: Quantum Computing at CLEF

• QuantumCLEF 2024: Overview of the Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF3032-3053
  Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro
  
• Towards a Hyperparameter-Free QUBO Formulation for Feature Selection in IR3054-3063
  Tiago Almeida, Sérgio Matos
  
• Team qIIMAS on Task 2 - Clustering3064-3074
  William Alvarez-Giron, Jorge Tellezz-Torres, Javier Tovar-Cortes, Helena Gómez-Adorno
  
• Team OpenWebSearch at CLEF 2024: QuantumCLEF3075-3081
  Maik Fröbe, Daria Alexander, Gijs Hendriksen, Ferdinand Schlatt, Matthias Hagen, Martin Potthast
  
• Quantum Feature Selection3082-3086
  Shimi Gersome, Jerin Mahibha, Durairaj Thenmozhi
  
• NICA at Quantum Computing CLEF Tasks 20243087-3095
  Aylin Naebzadeh, Sauleh Eetemadi
  
• CRUISE on Quantum Computing for Feature Selection in Recommender Systems3096-3104
  Jiayang Niu, Jie Li, Ke Deng, Yongli Ren
  
• Team QTB on Feature Selection Via Quantum Annealing and Hybrid Models3105-3114
  Esteban Payares, Edwin Puertas, Juan Carlos Martínez-Santos
  

SimpleText Lab: Improving Access to Scientific Texts for Everyone

• Overview of the CLEF 2024 SimpleText Task 1: Retrieve Passages to Include in a Simplified Summary3115-3128
  Eric Sanjuan, Stéphane Huet, Jaap Kamps, Liana Ermakova
  
• Overview of the CLEF 2024 SimpleText Task 2: Identify and Explain Difficult Concepts3129-3146
  Giorgio Maria Di Nunzio, Federica Vezzani, Vanessa Bonato, Hosein Azarbonyad, Jaap Kamps, Liana Ermakova
  
• Overview of the CLEF 2024 SimpleText Task 3: Simplify Scientific Text3147-3162
  Liana Ermakova, Valentin Laimé, Helen McCombie, Jaap Kamps
  
• Overview of the CLEF 2024 SimpleText Task 4: SOTA? Tracking the State-of-the-Art in Scholarly Publications3163-3173
  Jennifer D'Souza, Salomon Kabongo, Hamed Babaei Giglou, Yue Zhang
  
• Team Sharingans at SimpleText: Fine-tuned LLM based approach to Scientific Text Simplification3174-3181
  Syed Muhammad Ali, Hammad Sajid, Owais Aijaz, Owais Waheed, Faisal Alvi, Abdul Samad
  
• University of Amsterdam at the CLEF 2024 SimpleText Track3182-3194
  Jan Bakker, Göksenin Yüksel, Jaap Kamps
  
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 SimpleText Track: Scientific Text Made Simpler Through the Use of Artificial Intelligence3195-3205
  Antonia Bartulović, Dóra Paula Váradi
  
• Enhancing Scientific Document Simplification through Adaptive Retrieval and Generative Models3206-3229
  Artemis Capari, Hosein Azarbonyad, Zubair Afzal, Georgios Tsatsaronis
  
• UNIPD@SimpleText2024: A Semi-Manual Approach on Prompting ChatGPT for Extracting Terms and Write Terminological Definitions3230-3237
  Giorgio Maria Di Nunzio, Elena Gallina, Federica Vezzani
  
• AI Contributions to Simplifying Scientific Discourse in SimpleText 20243238-3245
  Regina Elagina, Petra Vučić
  
• Exploring the Latest LLMs for Leaderboard Extraction3246-3260
  Salomon Kabongo, Jennifer D'Souza, Sören Auer
  
• AIIR Lab Systems for CLEF 2024 SimpleText: Large Language Models for Text Simplification3261-3273
  Nicholas Largey, Reihaneh Maarefdoust, Shea Durgin, Behrooz Mansouri
  
• CLEF 2024 SimpleText Tasks 1-3: Use of Llama-2 for Text Simplification3274-3283
  Rowan Mann, Tomislav Mikulandric
  
• UZH Pandas at SimpleText2024: Multi-Prompt Minimum Bayes Risk with Diverse Prompts3284-3287
  Andrianos Michail, Pascal Severin Andermatt, Tobias Fankhauser
  
• SINAI Participation in SimpleText Task 2 at CLEF 2024: Zero-shot Prompting on GPT-4-Turbo for Lexical Complexity Prediction3288-3299
  Jenny Ortiz-Zambrano, César Espin-Riofrio, Arturo Montejo-Ráez
  
• AMATU@Simpletext2024: Are LLMs Any Good for Scientific Leaderboard Extraction?3300-3316
  Moritz Staudinger, Alaa El-Ebshihy, Annisa Maulida Ningtyas, Florina Piroi, Allan Hanbury
  
• UBO NLP Report on the SimpleText track at CLEF 20243317-3340
  Benjamin Vendeville, Liana Ermakova, Pierre De Loor
  

Touché: Argumentation Systems

• Overview of Touché 2024: Argumentation Systems3341-3366
  Johannes Kiesel, Çağrı Çöltekin, Maximilian Heinrich, Maik Fröbe, Milad Alshomary, Bertrand De Longueville, Tomaž Erjavec, Nicolas Handke, Matyáš Kopp, Nikola Ljubešić, Katja Meden, Nailia Mirzakhmedova, Vaidas Morkevičius, Theresa Reitis-Münstermann, Mario Scharfbillig, Nicolas Stefanovitch, Henning Wachsmuth, Martin Potthast, Benno Stein
  
• Team INSA Passau at Touché: Multi-lingual Parliamentary Speech Classification3367-3378
  Maud Andruszak, Alaa Alhamzeh, Elöd Egyed-Zsigmond, Anton Carlsson, Johan Leydet, Yasser Otiefy
  
• Edward Said at Touché: Human Value Detection Using Transformers and Upsampling3379-3383
  Aisha Nur Aydin, Shaden Shaar, Claire Cardie
  
• gerber at Touché: Ideology and Power Identification in Parliamentary Debates 20243384-3392
  Christian Gerber
  
• Pixel Phantoms at Touché: Ideology and Power Identification in Parliamentary Debates using Linear SVC3393-3400
  Janani Hariharakrishnan, Jithu Morrison S, P Mirunalini
  
• HTW-DIL at Touché: Multimodal Dense Information Retrieval for Arguments3401-3406
  Tamás Janukso, Aaron Kämpf, Denis Keiling, Jessica Knick, David Schäfer, Maik Thiele
  
• SCaLAR NITK at Touché: Comparative Analysis of Machine Learning Models for Human Value Identification3407-3413
  Praveen K, Darshan R K, Chinta Tejdeep Reddy, Anand Kumar M
  
• JU_NLP_DID at Touché: An Attempt to Identify Aspects of Power from Parliamentary Debates3414-3418
  Adnan Khurshid, Dipankar Das, Rajdeep Khaskel, Suchanda Datta
  
• Hierocles of Alexandria at Touché: Multi-task & Multi-head Custom Architecture with Transformer-based Models for Human Value Detection3419-3432
  Sotirios Legkas, Christina Christodoulou, Matthaios Zidianakis, Dimitrios Koutrintzes, Maria Dagioglou, Georgios Petasis
  
• Eric Fromm at Touché: Prompts vs FineTuning for Human Value Detection3433-3446
  Ranjan Mishra, Meike Morren
  
• DS@GT at Touché: Image Search and Ranking via CLIP and Image Generation3447-3450
  Benjamin Ostrower, Patcharapong Aphiwetsa
  
• Policy Parsing Panthers at Touché: Ideology and Power Identification in Parliamentary Debates3451-3477
  Oscar Palmqvist, Johan Jiremalm, Pablo Picazo-Sanchez
  
• Trojan Horses at Touché: Logistic Regression for Classification of Political Debates3478-3482
  Deepak Chandar S, Diya Seshan, Avaneesh Koushik, P Mirunalini
  
• Vayam Solve Kurmaha at Touché: Power Identification in Parliamentary Speeches Using TF-IDF Vectorizer and SVM Classifier3483-3488
  Lakshmi Priya S, Dhannya S M, S Shwetha, Surabhi Kamath, Shreedevi Seluka Balaji, Sai Nikitha N.S.R, Srinidhi Lakshmi Narayanan
  
• HALE Lab NITK at Touché 2024: A Hybrid Approach for Identifying Political Ideology and Power in Multilingual Parliamentary Speeches3489-3495
  Sevitha Simhadri, Mauli Mehulkumar Patel, Sowmya Kamath S.
  
• Ssnites at Touché: Ideology and Power Identification in Parliamentary Debates using BERT Mode3496-3502
  Keerthick V, Kaushik Ananth Kumar S, Kathir Kaman A, P Mirunalini, Sripriya N
  
• Philo of Alexandria at Touché: A Cascade Model Approach to Human Value Detection3503-3508
  Víctor Yeste, Mariona Coll-Ardanuy, Paolo Rosso
  
• Arthur Schopenhauer at Touché 2024: Multi-Lingual Text Classification Using Ensembles of Large Language Models3509-3517
  Hamza Yunis