7th International Conference on Natural Language Processing, Information Retrieval and AI (NIAI 2026)
March 14 ~ 15, 2026, Vienna, Austria Hybrid -- Registered authors can present their work online or face to face. Scope & Topics 7th International Conference on Natural Language Processing, Information Retrieval and AI (NIAI 2026) serves as a premier global forum for researchers, practitioners, and industry leaders to present cutting edge innovations at the intersection of NLP, IR, AI, Machine Learning, and Data Driven Technologies.
As AI systems rapidly evolve—from large language models and multimodal architectures to real world intelligent applications—the need for a unified platform that brings together diverse research communities has never been greater. NIAI 2026 aims to bridge these domains, fostering collaboration, advancing scientific understanding, and accelerating the development of responsible, impactful AI technologies.
The conference welcomes contributions that push theoretical boundaries, introduce novel methodologies, or demonstrate transformative applications across languages, modalities, and industries. With a strong emphasis on rigor, reproducibility, and societal relevance, NIAI aspires to stand alongside the world’s leading conferences in shaping the future of intelligent systems.
The Conference looks for significant contributions to all major fields of the Natural Language processing and machine learning in theoretical and practical aspects. Topics of interest include, but are not limited to, the following Artificial Intelligence & Machine Learning
- Foundations of Artificial Intelligence
- Deep Learning Architectures and Optimization
- Machine Learning for NLP and IR
- Reinforcement Learning and Sequential Decision Making
- Explainable, Responsible, and Trustworthy AI
- Federated, Distributed, and Privacy Preserving Learning
- Large Language Models (LLMs) and Foundation Models
- Retrieval Augmented Generation (RAG) and Memory Augmented Models
Natural Language Processing
- Syntax, Semantics, Pragmatics, and Discourse
- Text Classification, Summarization, and Generation
- Sentiment, Emotion, and Opinion Analysis
- Dialogue Systems, Conversational AI, and Chatbots
- Low Resource, Zero Shot, and Few Shot NLP
- NLP for Social Media and Short Form Content
- Evaluation Metrics, Benchmarking, and Reproducibility in NLP
Machine Translation & Multilingual Technologies
- Neural, Statistical, and Hybrid Machine Translation
- Cross lingual and Multilingual Representation Learning
- Code Switching and Multilingual Speech/Text Processing
- Language Preservation and NLP for Endangered Languages
Information Retrieval & Search Technologies
- Web Search, Ranking Models, and Relevance Estimation
- Neural IR and Deep Retrieval Models
- Query Understanding, Intent Modeling, and Personalization
- Recommender Systems and User Modeling
- Evaluation Frameworks and Reproducibility in IR
Big Data, Data Mining & Knowledge Technologies
- Big Data Analytics and Scalable AI Systems
- Knowledge Graphs, Ontologies, and Semantic Web
- Pattern Mining, Clustering, and Predictive Analytics
- Data Quality, Bias, Fairness, and Ethical Data Practices
Multimodal AI & Integrated Systems
- Vision Language Models (VLMs)
- Speech Text Vision Integration
- Image/Video Captioning and Multimodal Reasoning
- Embodied AI and Robotics Language Interfaces
Social Media, Networks & Computational Social Science
- Social Network Analysis and Graph based Learning
- Misinformation, Toxicity, and Online Safety
- Behavioral Modeling and Social Dynamics
- Computational Social Science and Digital Humanities
Speech & Spoken Language Processing
- Automatic Speech Recognition (ASR)
- Speech Synthesis and Voice Generation
- Spoken Dialogue Systems
- Prosody, Speaker Identification, and Emotion in Speech
Mobile, Edge & Ubiquitous AI
- AI for Mobile and Wireless Applications
- Edge Computing and On Device Intelligence
- IoT Driven Intelligent Systems
- Resource Efficient and Low Power AI Models
Cognitive Modeling& Human AI Interaction
- Human Centered NLP and IR
- Cognitive and Psycholinguistic Modeling
- Explainability, Interpretability, and User Trust
- Interactive and Adaptive AI Systems
AI Ethics, Safety & Societal Impact
- Fairness, Accountability, and Transparency
- Bias Detection and Mitigation
- AI Governance, Regulation, and Policy
- Societal, Cultural, and Economic Implications of AI
Applied AI & Interdisciplinary Applications
- AI for Healthcare, Education, Finance, and Law
- Biomedical NLP and Clinical Text Mining
- AI for Climate, Sustainability, and Environmental Modeling
- Industrial Applications and Production Scale AI Systems
Emerging Trends & Future Directions
- Hybrid NeuralSymbolic Systems
- Continual, Lifelong, and Meta Learning
- Autonomous Agents and Multi Agent Systems
- Novel Benchmarks, Datasets, and Evaluation Paradigms
Paper Submission Authors are invited to submit papers through the conference Submission System by March 07, 2026(Final Call). Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings (H index 45) in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from NIAI 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | March 07, 2026(Final Call) | | Authors Notification | : | March 10, 2026 | | Final Manuscript Due | : | March 11, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to niai@ccseit2026.org
|
