Paper
Submissions addressing novel techniques for detecting, classifying, and modeling multimedia content under cross-domain, cross-lingual, and cross-modal settings, with a focus on agentic applications and low-resource contexts.
AI/CORE Unranked
LC4 SPELLL2026 2026
Fifth workshop on Low Resource Cross Domain, Cross Lingual, Cross Modal Content Analysis (LC4) @ SPELLL 2026
The Fifth Workshop on Low Resource Cross-Domain, Cross-Lingual, and Cross-Modal Content Analysis (LC4 2026) focuses on novel computational methods for analyzing multimedia content in low-resource settings, with an emphasis on agentic AI, multilingual learning, and responsible AI. It invites submissions leveraging foundational models like LLMs and vision-language models for robust, interpretable, and socially impactful content analysis across domains, languages, and modalities.
Key deadlines
Verified September 9, 2026Full paper
August 30, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
August 30, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Agentic AI & Autonomous Multimodal Intelligence
Agentic workflows for multilingual analysisLarge Language Models (LLMs)Vision-Language Foundation Models (VLMs)Speech Foundation ModelsRetrieval-Augmented Generation (RAG)Agentic AI for multimedia analysisMulti-agent collaboration for content understandingParameter-efficient fine-tuning and prompting strategiesMultimodal document intelligenceOCR and document understanding for low-resource scripts
02
Low-Resource and Cross-Lingual Learning
Multilingual and low-resource language modelsTransfer learning for underrepresented languagesCross-lingual retrieval and semantic alignmentMultilingual summarization, question answering, and information extractionCode-mixed misinformation detectionCross-lingual knowledge transferSynthetic data generationIndigenous and endangered language resources
03
Human-Centered and Responsible AI
Human–AI collaborative fact-checkingAnnotation quality and consensus modelingBias and fairness in moderation systemsPrivacy-preserving misinformation analysisTransparent and interpretable AI systemsEthical deployment in sensitive contexts
Policies worth checking twice
- Submission is open via OpenReview
- Mode: In-person workshop with remote presentation option for participants who cannot travel
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026