|
| |||||||||||||||
CFP SS CAI 2026 : CFP SS Emerging Trends in Data, Web, and Social Media Analysis and Generation with LLMs (CAI 2026) | |||||||||||||||
| Link: https://www.ieeesmc.org/cai-2026/ | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
|
IEEE Conference on Artificial Intelligence 2026 (IEEE CAI 2026)
May 8-10 2026 in Granada (Spain) https://www.ieeesmc.org/cai-2026/ SPECIAL SESSION “Emerging Trends in Data, Web, and Social Media Analysis and Generation with LLMs” SESSION CODE: Please use the following code when submitting your paper to this session: SS2-LLMS DESCRIPTION This session focuses on the transformative role of large language models (LLMs) in enabling advanced analysis and generation of data from the web and social media. It aims to bring together researchers, practitioners, and industry experts interested in how LLMs are reshaping our ability to interpret, summarize, retrieve, and generate content across large-scale, unstructured, and dynamic data environments. Contributions are welcome from both theoretical and applied perspectives, covering novel methodologies, system architectures, and real-world applications. The session also encourages submissions that address critical issues related to transparency, ethics, and responsible use of LLMs in open and high-impact domains. TOPICS OF INTEREST - LLMs for Social Media Analysis. Investigating the use of LLMs to extract insights from social media platforms, including sentiment and stance detection, topic modelling, misinformation identification, and audience analysis. - Text Understanding and Knowledge Extraction with LLMs. Approaches leveraging LLMs for summarization, classification, information extraction, question answering, and retrieval-augmented generation (RAG) over complex and noisy text sources. - Multimodal and Hybrid LLM Applications. Integration of LLMs with other data modalities (e.g., visual, audio, structured data) or symbolic systems to enhance performance in cross-domain analysis and interactive AI systems. - Real-Time and Context-Aware Processing. Using LLMs for streaming data analysis, adaptive content generation, and real-time decision support, particularly in fast-changing web and social media environments. - Ethics, Safety, and Responsible Deployment of LLMs. Exploring issues of fairness, bias, explainability, and user privacy in LLM-based applications, with emphasis on accountability and trustworthy AI in high-impact contexts. TARGET AUDIENCE This session is intended for researchers, practitioners, data scientists, and industry experts working in LLMs, generative AI, and web/data analysis, with a particular focus on applications to social media and text data analysis. It also welcomes professionals interested in the ethical, methodological, and practical implications of applying LLMs and generative AI to data-driven decision-making. ORGANIZERS M. Dolores Ruiz (mariloruiz@ugr.es) Maria J. Martin-Bautista (mbautis@decsai.ugr.es) Computer Science and A.I. Department, University of Granada (Spain) IMPORTANT DATES Paper submission: November 15, 2025 Paper Evaluations to Authors: December 15, 2025 Final Camera Ready & Registration: January 20, 2026 Conference: May 08-10, 2026 SUBMISSION, AUTHOR INSTRUCTIONS AND TEMPLATES https://www.ieeesmc.org/cai-2026/author-instructions-and-templates-for-conference-proceedings/ |
|