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ORCIDCLEF 2024: Grenoble, France - Working Notes
- Guglielmo Faggioli, Nicola Ferro, Petra Galuscáková, Alba García Seco de Herrera:
Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024), Grenoble, France, 9-12 September, 2024. CEUR Workshop Proceedings 3740, CEUR-WS.org 2024
BioASQ: Large-scale Biomedical Semantic Indexing and Question Answering
- Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara, Georgios Paliouras:
Overview of BioASQ Tasks 12b and Synergy12 in CLEF2024. 1-7 - Salvador Lima-López, Eulàlia Farré-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 MultiCardioNER task at BioASQ 2024 on Medical Specialty and Language Adaptation of Clinical NER Systems for Spanish, English and Italian. 8-27 - Vera Davydova, Natalia V. Loukachevitch, Elena Tutubalina:
Overview of BioNNE Task on Biomedical Nested Named Entity Recognition at BioASQ 2024. 28-34 - Anna Aksenova, Aleksis Datseris, Sylvia Vassileva, Svetla Boytcheva:
Transformer-Based Disease and Drug Named Entity Recognition in Multilingual Clinical Texts: MultiCardioNER challenge. 35-46 - Tiago Almeida, Richard A. A. Jonker, João António Reis, João Rafael Almeida, Sérgio Matos:
BIT.UA at BioASQ 12: From Retrieval to Answer Generation. 47-67 - Christopher Anaya, Maria Fernandes, Francisco M. Couto:
LLM Fine-Tuning With Biomedical Open-Source Data. 68-77 - Samy Ateia, Udo Kruschwitz:
Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks. 78-98 - Bing-Chen Chih, Jen-Chieh Han, Richard Tzong-Han Tsai:
NCU-IISR: Enhancing Biomedical Question Answering with GPT-4 and Retrieval Augmented Generation in BioASQ 12b Phase B. 99-105 - Manuela Daniela Danu, George Marica, Constantin Suciu, Lucian Mihai Itu, Oladimeji Farri:
Multilingual Clinical NER for Diseases and Medications Recognition in Cardiology Texts using BERT Embeddings. 106-116 - Yichen Gao, Licheng Zong, Yu Li:
Enhancing Biomedical Question Answering with Parameter-Efficient Fine-Tuning and Hierarchical Retrieval Augmented Generation. 117-129 - Rodrigo Gonçalves, André Lamúrias:
Team NOVA LINCS @ BIOASQ12 MultiCardioNER Track: Entity Recognition with Additional Entity Types. 130-137 - Bor-Woei Huang:
Generative Large Language Models Augmented Hybrid Retrieval System for Biomedical Question Answering. 138-149 - Richard A. A. Jonker, Tiago Almeida, Sérgio Matos:
BIT.UA at MultiCardioNER: Adapting a Multi-head CRF for Cardiology. 150-158 - Chaeeun Lee, T. Ian Simpson, Joram M. Posma, Antoine D. Lain:
Comparative Analyses of Multilingual Drug Entity Recognition Systems for Clinical Case Reports In Cardiology. 159-167 - Maël Lesavourey, Gilles Hubert:
Enhancing Biomedical Document Ranking with Domain Knowledge Incorporation in a Multi-Stage Retrieval Approach. 168-175 - Jan Heinrich Merker, Alexander Bondarenko, Matthias Hagen, Adrian Viehweger:
MiBi at BioASQ 2024: Retrieval-Augmented Generation for Answering Biomedical Questions. 176-187 - Dimitra N. Panou, Alexandros C. Dimopoulos, Martin Reczko:
Farming Open LLMs for Biomedical Question Answering. 188-196 - Hasin Rehana, Benu Bansal, Nur Bengisu Çam, Jie Zheng, Yongqun He, Arzucan Özgür, Junguk Hur:
Nested Named Entity Recognition using Multilayer BERT-based Model. 197-206 - Antonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato:
Identifying Cardiological Disorders in Spanish via Data Augmentation and Fine-Tuned Language Models. 207-222 - Patrick Styll, Leonardo Campillos Llanos, Wojciech Kusa, Allan Hanbury:
Cross-Linguistic Disease and Drug Detection in Cardiology Clinical Texts: Methods and Outcomes. 223-244 - Wenxin Zhou:
Biomedical Nested NER with Large Language Model and UMLS Heuristics. 245-252 - Wenxin Zhou, Thuy Hang Ngo:
Using Pretrained Large Language Model with Prompt Engineering to Answer Biomedical Questions. 253-268 - Oguz Serbetçi, Xing David Wang, Ulf Leser:
HU-WBI at BioASQ12B Phase A: Exploring Rank Fusion of Dense Retrievers and Re-rankers. 269-275
CheckThat!: Predicting Check-Worthiness, Subjectivity, Persuasion, Roles and Authorities
- 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 1 on Check-Worthiness Estimation of Multigenre Content. 276-286 - Julia Maria Struß, Federico Ruggeri, Alberto Barrón-Cedeño, Firoj Alam, Dimitar Dimitrov, 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 2 on Subjectivity in News Articles. 287-298 - Jakub Piskorski, Nicolas Stefanovitch, Firoj Alam, Ricardo Campos, Dimitar Dimitrov, Alípio Jorge, Senja Pollak, Nikolay Ribin, Zoran Fijavz, 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 3 on Persuasion Techniques. 299-310 - Fatima Haouari, Tamer Elsayed, Reem Suwaileh:
Overview of the CLEF-2024 CheckThat! Lab Task 5 on Rumor Verification using Evidence from Authorities. 311-320 - Piotr Przybyla, Ben Wu, Alexander V. Shvets, Yida Mu, Kim Cheng Sheang, Xingyi Song, Horacio Saggion:
Overview of the CLEF-2024 CheckThat! Lab Task 6 on Robustness of Credibility Assessment with Adversarial Examples (InCrediblAE). 321-338 - Peter Røysland Aarnes, Vinay Setty, Petra Galuscáková:
IAI Group at CheckThat! 2024: Transformer models and data augmentation for checkworthy claim detection. 339-350 - Sayanta Adhikari, Himanshu Sharma, Rupa Kumari, Shrey Satapara, Maunendra Desarkar:
DEFAULT at CheckThat! 2024: Retrieval Augmented Classification using Differentiable Top-K Operator for Rumor Verification based on Evidence from Authorities. 351-360 - Md. Rafiul Biswas, Abrar Tasneem Abir, Wajdi Zaghouani:
Nullpointer at CheckThat! 2024: Identifying Subjectivity from Multilingual Text Sequence. 361-368 - Mehmet Eren Bulut, Kaan Efe Keles, Mucahid Kutlu:
TurQUaz at CheckThat! 2024: A Hybrid Approach of Fine-Tuning and In-Context Learning for Check-Worthiness Estimation. 369-377 - Morgane Casanova, Julien Chanson, Benjamin Icard, Géraud Faye, Guillaume Gadek, Guillaume Gravier, Paul Égré:
HYBRINFOX at CheckThat! 2024 - Task 2: Enriching BERT Models with the Expert System VAGO for Subjectivity Detection. 378-386 - Md. Sajid Alam Chowdhury, Anik Mahmud Shanto, Mostak Mahmud Chowdhury, Hasan Murad, Udoy Das:
Fired_from_NLP at CheckThat! 2024: Estimating the Check-Worthiness of Tweets Using a Fine-tuned Transformer-based Approach. 387-395 - Basak Demirok, Selin Mergen, Bugra Oz, Mucahid Kutlu:
TurQUaz at CheckThat! 2024: Creating Adversarial Examples using Genetic Algorithm. 396-404 - Mirela Dryankova, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov:
Mirela at CheckThat! 2024: Check-worthiness of Tweets with Multilingual Embeddings and Adversarial Training. 405-410 - Géraud Faye, Morgane Casanova, Benjamin Icard, Julien Chanson, Guillaume Gadek, Guillaume Gravier, Paul Egré:
HYBRINFOX at CheckThat! 2024 - Task 1: Enhancing Language Models with Structured Information for Check-Worthiness Estimation. 411-418 - Ewelina Gajewska:
Eevvgg at CheckThat! 2024: Evaluative Terms, Pronouns and Modal Verbs as Markers of Subjectivity in Text. 419-425 - Paolo Gajo, Luca Giordano, Alberto Barrón-Cedeño:
UniBO at CheckThat! 2024: Multi-lingual and Multi-label Persuasion Technique Detection in News with Data Augmentation and Sequence-Token Classifiers. 426-434 - Pawel Golik, Arkadiusz Modzelewski, Aleksander Jochym:
DSHacker at CheckThat! 2024: LLMs and BERT for Check-Worthy Claims Detection with Propaganda Co-occurrence Analysis. 435-445 - Shayne Gruman, Leila Kosseim:
CLaC-2 at CheckThat! 2024: A Zero-Shot Model for Check-Worthiness and Subjectivity Classification. 446-452 - David Guzman Piedrahita, Arnisa Fazla, Lucas Krauter:
TextTrojaners at CheckThat! 2024: Robustness of Credibility Assessment with Adversarial Examples through BeamAttack. 453-472 - Haokun He, Yafeng Song, Dylan Massey:
Palöri at CheckThat! 2024 Shared Task 6: GloTa - Combining GloVe Embeddings with RoBERTa for Adversarial Attack. 473-482 - Sanjai Balajee Kannan Giridharan, Sanjjit Sounderrajan, B. Bharathi, Nilu R. Salim:
SSN-NLP at CheckThat! 2024: Assessing the Check-Worthiness of Tweets and Debate Excerpts Using Traditional Machine Learning and Transformer Models. 483-488 - Luis Kolb, Allan Hanbury:
AuthEv-LKolb at CheckThat! 2024: A Two-Stage Approach To Evidence-Based Social Media Claim Verification. 489-505 - Wlodzimierz Lewoniewski, Piotr Stolarski, Milena Strózyna, Elzbieta Lewanska, Aleksandra Wojewoda, Ewelina Ksiezniak, Marcin Sawinski:
OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text Generation. 506-519 - Yufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga:
FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruning. 520-537 - Sai Geetha M, Prarthna M, Chiranjeev Prasannaa V. V, Saritha M:
Trio Titans at Check That_ 2024 : Check Worthiness Estimation. 538-545 - Sara Nabhani, Md Abdur Razzaq Riyadh:
Mela at CheckThat! 2024: Transferring Persuasion Detection from English to Arabic - A Multilingual BERT Approach. 546-551 - Ashraful Islam Paran, Md. Sajjad Hossain, Symom Hossain Shohan, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque:
SemanticCuetSync at CheckThat! 2024: Finding Subjectivity in News Articles using Llama. 552-559 - Andrea Pasin, Nicola Ferro:
SEUPD@CLEF: Team Axolotl on Rumor Verification using Evidence from Authorities. 560-569 - Pooja Premnath, Pranav Vaithiya Subramani, Nilu R. Salim, Bharathi B:
SSN-NLP at CheckThat! 2024: From Feature-based Algorithms to Transformers: A Study on Detecting Subjectivity. 570-579 - Charlie Roadhouse, Matthew Shardlow, Ashley Williams:
MMU NLP at CheckThat! 2024: Homoglyphs are Adversarial Attacks. 580-589 - Antonio Rodríguez, Elisabet Golobardes, Jaume Suau:
Tonirodriguez at CheckThat!2024: Is it Possible to Use Zero-Shot Cross-Lingual Methods for Subjectivity Detection in Low-Resources Languages? 590-597 - Karla Salas-Jimenez, Iván Díaz, Helena Gómez-Adorno, Gemma Bel-Enguix, Gerardo Sierra:
JK_PCIC_UNAM at CheckThat! 2024: Analysis of Subjectivity in News Sentences Using Transformers-Based Models. 598-604 - Soumyadeep Sar, Dwaipayan Roy:
Indigo at CheckThat! 2024: Using Setfit: A Resource Efficient Technique for Subjectivity Detection in News Article. 605-612 - Marcin Sawinski, Krzysztof Wecel, Ewelina Ksiezniak:
OpenFact at CheckThat! 2024: Cross-Lingual Transfer Learning for Check-Worthiness Detection. 613-631 - Symom Hossain Shohan, Md. Sajjad Hossain, Ashraful Islam Paran, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque:
SemanticCuetSync at CheckThat! 2024: Pre-trained Transformer-based Approach to Detect Check-Worthy Tweet. 632-640 - Tanisha Sriram, Yadushree Venkatesh, Sowmya Anand, Bharathi B:
DataBees at CheckThat! 2024: Check-Worthiness Estimation. 641-650 - Sergiu Stoia, Jaime Collado-Montañez, Cristian Ibáñez-Bautista, Arturo Montejo-Ráez, María Teresa Martín-Valdivia, Manuel Carlos Díaz-Galiano:
SINAI at CheckThat! 2024: Transformer-based Approaches for Check-Worthiness Classification. 651-657 - José Valle-Aguilera, Alberto José Gutiérrez-Megías, Salud María Jiménez-Zafra, Luis Alfonso Ureña López, Eugenio Martínez-Cámara:
SINAI at CheckThat! 2024: Stealthy Character-Level Adversarial Attacks Using Homoglyphs and Iterative Search. 658-665 - Inna Vogel, Pauline Möhle:
Fraunhofer SIT at CheckThat! 2024: Adapter Fusion for Check-Worthiness Detection. 666-671 - Sanne Weering, Tommaso Caselli:
FC_RUG at CheckThat! 2024: Few-shot Learning Using GEITje for Check-Worthiness Detection in Dutch. 672-679 - Syeda Duae Zehra, Kushal Chandani, Muhammad Khubaib, Ahmed Ali Aun Muhammed, Faisal Alvi, Abdul Samad:
Checker Hacker at CheckThat! 2024: Detecting Check-Worthy Claims and Analyzing Subjectivity with Transformers. 680-686
ELOQUENT: Evaluating Generative Language Models
- Jussi Karlgren, Aarne Talman:
ELOQUENT 2024 - Topical Quiz Task. 687-690 - Luise Dürlich, Evangelia Gogoulou, Liane Guillou, Joakim Nivre, Shorouq Zahra:
Overview of the CLEF-2024 Eloquent Lab: Task 2 on HalluciGen. 691-702 - Magnus Sahlgren, Jussi Karlgren, Luise Dürlich, Evangelia Gogoulou, Aarne Talman, Shorouq Zahra:
ELOQUENT 2024 - Robustness Task. 703-707 - Vasumathi Neralla, Sander Bijl de Vroe:
Evaluating Poro-34B-Chat and Mistral-7B-Instruct-v0.1: LLM System Description for ELOQUENT at CLEF 2024. 708-711 - Marco Siino, Ilenia Tinnirello:
GPT Hallucination Detection Through Prompt Engineering. 712-721 - Annika Simonsen:
Experimental Report on Robustness Task - ELOQUENT Lab @ CLEF 2024. 722-726 - Anh Thu Maria Bui, Saskia Felizitas Brech, Natalie Hußfeldt, Tobias Jennert, Melanie Ullrich, Timo Breuer, Narjes Nikzad-Khasmakhi, Philipp Schaer:
The Two Sides of the Coin: Hallucination Generation and Detection with LLMs as Evaluators for LLMs. 727-758
eRisk 2024: Early Risk Prediction on the Internet
- Javier Parapar, Patricia Martín-Rodilla, David E. Losada, Fabio Crestani:
Overview of eRisk 2024: Early Risk Prediction on the Internet (Extended Overview). 759-781 - Beng Heng Ang, Sujatha Das Gollapalli, See-Kiong Ng:
NUS-IDS@eRisk2024: Ranking Sentences for Depression Symptoms using Early Maladaptive Schemas and Ensembles. 782-793 - Anna Barachanou, Filareti Tsalakanidou, Symeon Papadopoulos:
REBECCA at eRisk 2024: Search for Symptoms of Depression Using Sentence Embeddings and Prompt-Based Filtering. 794-802 - Andreu Casamayor, Vicent Ahuir, Antonio Molina, Lluís-Felip Hurtado:
ELiRF-VRAIN at eRisk 2024: Using LongFormers for Early Detection of Signs of Anorexia. 803-812 - Hermenegildo Fabregat, Daniel Deniz, Andrés Duque, Lourdes Araujo, Juan Martínez-Romo:
NLP-UNED at eRisk 2024: Approximate Nearest Neighbors with Encoding Refinement for Early Detecting Signs of Anorexia. 813-824 - David Guecha, Aaryan Potdar, Anthony Miyaguchi:
DS@GT eRisk 2024: Sentence Transformers for Social Media Risk Assessment. 825-833 - Raluca-Maria Hanciu:
MindwaveML at eRisk 2024: Identifying Depression Symptoms in Reddit Users. 834-840 - Diego Maupomé, Yves Ferstler, Sébastien Mosser, Marie-Jean Meurs:
Automatically Finding Evidence and Predicting Answers in Mental Health Self-Report Questionnaires. 841-850 - Alba María Mármol-Romero, Adrián Moreno-Muñoz, Pablo Álvarez-Ojeda, Karla María Valencia-Segura, Eugenio Martínez-Cámara, Manuel García Vega, Arturo Montejo-Ráez:
SINAI at eRisk@ CLEF 2024: Approaching the Search for Symptoms of Depression and Early Detection of Anorexia Signs using Natural Language Processing. 851-861 - Ronghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García:
UMUTeam at eRisk@CLEF 2024: Fine-Tuning Transformer Models with Sentiment Features for Early Detection and Severity Measurement of Eating Disorders. 862-870 - Alejandro Pardo Bascuñana, Isabel Segura-Bedmar:
APB-UC3M at eRisk 2024: Natural Language Processing and Deep Learning for the Early Detection of Mental Disorders. 871-880 - Sachin Prasanna, Abhayjit Singh Gulati, Subhojit Karmakar, M. Yoga Hiranmayi, Anand Kumar Madasamy:
Measuring the severity of the signs of Eating Disorders using Machine Learning Techniques. 881-887 - Oskar Riewe-Perla, Agata Filipowska:
Combining Recommender Systems and Language Models in Early Detection of Signs of Anorexia. 888-893 - Prateek Sarangi, Sumit Kumar, Shraddha Agarwal, Tanmay Basu:
A Natural Language Processing Based Framework for Early Detection of Anorexia via Sequential Text Processing. 894-901 - Horacio Thompson, Marcelo Errecalde:
A Time-Aware Approach to Early Detection of Anorexia: UNSL at eRisk 2024. 902-907
EXIST: sEXism Identification in Social neTworks
- Laura Plaza, Jorge Carrillo de Albornoz, Víctor Ruiz, Alba Maeso, Berta Chulvi, Paolo Rosso, Enrique Amigó, Julio Gonzalo, Roser Morante, Damiano Spina:
Overview of EXIST 2024 - Learning with Disagreement for Sexism Identification and Characterization in Tweets and Memes (Extended Overview). 908-941 - Giacomo Aru, Nicola Emmolo, Simone Marzeddu, Andrea Piras, Jacopo Raffi, Lucia C. Passaro:
RoBEXedda: Sexism Detection in Tweets. 942-957 - AmirMohammad Azadi, Baktash Ansari, Sina Zamani, Sauleh Eetemadi:
Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot Learning. 958-965 - Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Fabiha Haider, Fariha Tanjim Shifat, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan:
Penta ML at EXIST 2024: Tagging Sexism in Online Multimodal Content With Attention-enhanced Modal Context. 966-977 - Álvaro Carrillo-Casado, Javier Román Pásaro, Jacinto Mata Vázquez, Victoria Pachón Álvarez:
I2C-UHU at EXIST 2024: Transformer-Based Detection of Sexism and Source Intention in Memes Using a Learning with Disagreement Approach. 978-992 - Shiying Fan, Raphael Antonius Frick, Martin Steinebach:
FraunhoferSIT@EXIST2024: Leveraging Stacking Ensemble Learning for Sexism Detection. 993-1002 - Yi-Zeng Fang, Lung-Hao Lee, Juinn-Dar Huang:
NYCU-NLP at EXIST 2024: Leveraging Transformers with Diverse Annotations for Sexism Identification in Social Networks. 1003-1011 - Arnau García i Cucó, Miquel Obrador Reina:
LightGBM for Sexism Identification in Memes. 1012-1017 - Gersome Shimi, Jerin Mahibha C, Durairaj Thenmozhi:
Automatic Classification of Gender Stereotypes in Social Media Post. 1018-1025 - Manuel Guerrero-García, Manuel Cerrejón-Naranjo, Jacinto Mata Vázquez, Victoria Pachón Álvarez:
I2C-UHU at EXIST2024: Learning from Divergence and Perspectivism for Sexism Identification and Source Intent Classification. 1026-1042 - Martha Paola Jimenez-Martinez, Joan Manuel Raygoza-Romero, Carlos Eduardo Sánchez-Torres, Irvin Hussein López-Nava, Manuel Montes-y-Gómez:
Enhancing Sexism Detection in Tweets with Annotator-Integrated Ensemble Methods and Multimodal Embeddings for Memes. 1043-1057 - Ron Keinan:
Sexism Identification in Social Networks using TF-IDF Embeddings, PreProccessing, Feature Selection, Word/Char N-Grams and Various Machine Learning Models In Spanish and English. 1058-1069 - Sahrish Khan, Gabriele Pergola, Arshad Jhumka:
Multilingual Sexism Identification via Fusion of Large Language Models. 1070-1079 - Jing Ma, Rong Li:
RoJiNG-CL at EXIST 2024: Leveraging Large Language Models for Multimodal Sexism Detection in Memes. 1080-1090 - Fariha Maqbool, Elisabetta Fersini:
A Contrastive Learning Based Approach to Detect Sexism in Memes. 1091-1097 - Nimra Maqbool:
Sexism Identification in Social Networks: Advances in Automated Detection - A Report on the Exist Task at CLEF. 1098-1106 - Elizabeth Martinez, Juan Cuadrado, Juan Carlos Martínez Santos, Edwin Puertas:
VerbaNex AI at CLEF EXIST 2024: Detection of Online Sexism using Transformer Models and Profiling Techniques. 1107-1113 - Aitana Menárguez-Box, Diego Torres-Bertomeu:
DiTana-PV at sEXism Identification in Social neTworks (EXIST) tasks 4 and 6: The Effect of Translation in Sexism Identification. 1114-1121 - Aylin Naebzadeh, Melika Nobakhtian, Sauleh Eetemadi:
NICA at EXIST CLEF Tasks 2024. 1122-1134 - Ronghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García:
UMUTeam at EXIST 2024: Multi-modal Identification and Categorization of Sexism by Feature Integration. 1135-1147 - Umera Wajeed Pasha:
Multilingual Sexism Detection in Memes, A CLIP-Enhanced Machine Learning Approach. 1148-1156 - Alexandru Petrescu, Ciprian-Octavian Truica, Elena Simona Apostol:
Language-based Mixture of Transformers for EXIST2024. 1157-1164 - Le Minh Quan, Dang Van Thin:
Sexism Identification in Social Networks with Generation-based Language Models. 1165-1176 - Giulia Rizzi, David Gimeno-Gómez, Elisabetta Fersini, Carlos D. Martínez-Hinarejos:
PINK at EXIST2024: A Cross-Lingual and Multi-Modal Transformer Approach for Sexism Detection in Memes. 1177-1186 - Víctor Ruiz, Jorge Carrillo-de-Albornoz, Laura Plaza:
Concatenated Transformer Models Based On Levels Of Agreements For Sexism Detection. 1187-1197 - Aditya Shah, Aditya Gokhale:
Team Aditya at EXIST 2024 - Detecting Sexism in Multilingual Tweets using Contrastive Learning Approach. 1198-1202 - Abhay Shanbhag, Suramya Jadhav, Atharva Date, Sumedh Joshi, Sheetal Sonawane:
The Wisdom of Weighing: Stacking Ensembles for a More Balanced Sexism Detector. 1203-1213 - Fariha Tanjim Shifat, Fabiha Haider, Md Sakib Ul Rahman Sourove, Deeparghya Dutta Barua, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan:
Penta-nlp at EXIST 2024 Task 1-3: Sexism Identification, Source Intention, Sexism Categorization In Tweets. 1214-1227 - Marco Siino, Ilenia Tinnirello:
Prompt Engineering for Identifying Sexism using GPT Mistral 7B. 1228-1236 - Tony Smith, H. Ruda Nie, Johanne R. Trippas, Damiano Spina:
RMIT-IR at EXIST Lab at CLEF 2024. 1237-1252 - Murari Sreekumar, Shreyas Karthik, Durairaj Thenmozhi, Shriram Gopalakrishnan, Krithika Swaminathan:
Sexism Identification in Tweets Using Machine Learning Approaches. 1253-1259 - Judith Tavarez-Rodríguez, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy:
Better Together: LLM and Neural Classification Transformers to Detect Sexism. 1260-1273 - Maha Usmani, Rania Siddiqui, Samin Rizwan, Faryal Khan, Faisal Alvi, Abdul Samad:
Sexism Identification in Tweets using BERT and XLM - Roberta. 1274-1279 - Advaitha Vetagiri, Prateek Mogha, Partha Pakray:
Cracking Down on Digital Misogyny with MULTILATE a MULTImodaL hATE Detection System. 1280-1296 - Kapioma Villarreal Haro, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy:
Stacked Reflective Reasoning in Large Neural Language Models. 1297-1311
iDPP: Intelligent Disease Progression Prediction
- 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 García 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:
Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. 1312-1331 - Guido Barducci, Flavio Sartori, Giovanni Birolo, Tiziana Sanavia, Piero Fariselli:
ALSFRS-R Score Prediction for Amyotrophic Lateral Sclerosis. 1332-1340 - Pietro Bosoni, Mahin Vazifehdan, Daniele Pala, Eleonora Tavazzi, Roberto Bergamaschi, Riccardo Bellazzi, Arianna Dagliati:
Predicting Multiple Sclerosis Relapses Using Patient Exposure Trajectories. 1341-1352 - Elena Marinello, Alessandro Guazzo, Enrico Longato, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo:
Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative Study. 1353-1365 - Andreia S. Martins, Daniela M. Amaral, Eduardo N. Castanho, Diogo F. Soares,