Results 251 to 260 of about 21,648 (265)

SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity Representation

arXiv.org
Idiomatic expressions present a unique challenge in NLP, as their meanings are often not directly inferable from their constituent words. Despite recent advancements in Large Language Models (LLMs), idiomaticity remains a significant obstacle to robust ...
Thomas Mark Rodbourn Pickard, Aline Villavicencio, Maggie Mi, Wei He, Dylan Phelps, Carolina Scarton, M. Idiart   +6 more
semanticscholar   +1 more source

Semeval 2007 task 18

Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007
In this paper, we present the details of the Arabic Semantic Labeling task. We describe some of the features of Arabic that are relevant for the task. The task comprises two subtasks: Arabic word sense disambiguation and Arabic semantic role labeling. The task focuses on modern standard Arabic.
Mona Diab, Musa Alkhalifa, Sabri Elkateb, Christiane Fellbaum, Aous Mansouri, Martha Palmer   +5 more
openaire   +1 more source

SemEval-2025 Task 5: LLMs4Subjects - LLM-based Automated Subject Tagging for a National Technical Library's Open-Access Catalog

arXiv.org
We present SemEval-2025 Task 5: LLMs4Subjects, a shared task on automated subject tagging for scientific and technical records in English and German using the GND taxonomy.
Jennifer D'Souza, Sameer Sadruddin, H. Israel, M. Begoin, Diana Slawig   +4 more
semanticscholar   +1 more source

SemEval-2024 Task 4: Multilingual Detection of Persuasion Techniques in Memes

International Workshop on Semantic Evaluation
The automatic identification of misleading and persuasive content has emerged as a significant issue among various stakeholders, including social media platforms, policymakers, and the broader society. To tackle this issue within the context of memes, we
Dimitar I. Dimitrov, Firoj Alam, Maram Hasanain, A. Hasnat, Fabrizio Silvestri, Preslav Nakov, Giovanni Da San Martino   +6 more
semanticscholar   +1 more source

SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection

arXiv.org
We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource and are spoken across various continents.
Shamsuddeen Hassan Muhammad, Nedjma Djouhra Ousidhoum, Idris Abdulmumin, Seid Muhie Yimam, Jan Philip Wahle, Terry Ruas, Meriem Beloucif, Christine de Kock, Tadesse Destaw Belay, I. Ahmad, Nirmal Surange, Daniela Teodorescu, David Ifeoluwa Adelani, Alham Fikri Aji, Felermino Ali, Vladimir Araujo, A. Ayele, Oana Ignat, Alexander Panchenko, Yi Zhou, Saif Mohammad   +20 more
semanticscholar   +1 more source

SemEval-2025 Task 9: The Food Hazard Detection Challenge

arXiv.org
In this challenge, we explored text-based food hazard prediction with long tail distributed classes. The task was divided into two subtasks: (1) predicting whether a web text implies one of ten food-hazard categories and identifying the associated food ...
Korbinian Randl, John Pavlopoulos, Aron Henriksson, Tony Lindgren, Juli Bakagianni   +4 more
semanticscholar   +1 more source

SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

International Workshop on Semantic Evaluation
We present the results and the main findings of SemEval-2024 Task 8: Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. The task featured three subtasks. Subtask A is a binary classification task determining whether a text is
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, A. Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Chenxi Whitehouse, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, Preslav Nakov   +14 more
semanticscholar   +1 more source

SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials

International Workshop on Semantic Evaluation
Large Language Models (LLMs) are at the forefront of NLP achievements but fall short in dealing with shortcut learning, factual inconsistency, and vulnerability to adversarial inputs.
Mael Jullien, Marco Valentino, André Freitas   +2 more
semanticscholar   +1 more source

SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations

International Workshop on Semantic Evaluation
The ability to understand emotions is an essential component of human-like artificial intelligence, as emotions greatly influence human cognition, decision making, and social interactions.
Fanfan Wang, Heqing Ma, Jianfei Yu, Rui Xia, Erik Cambria   +4 more
semanticscholar   +1 more source

SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)

International Workshop on Semantic Evaluation
We present SemEval-2024 Task 10, a shared task centred on identifying emotions and finding the rationale behind their flips within monolingual English and Hindi-English code-mixed dialogues.
Shivani Kumar, Md. Shad Akhtar, Erik Cambria, Tanmoy Chakraborty   +3 more
semanticscholar   +1 more source