7th International Conference on Advanced Natural Language Processing (AdNLP 2026)
June 20 ~ 21, 2026, Sydney, Australia Hybrid -- Registered authors can present their work online or face to face. Scope & Topics 7th International Conference on Advanced Natural Language Processing (AdNLP 2026) serves as a premier global forum for researchers, practitioners and industry innovators to exchange cutting edge insights in the rapidly evolving field of Natural Language Processing. As NLP continues to transform the landscape of artificial intelligence, driving advancements in communication, knowledge discovery, and intelligent systems, AdNLP 2026 provides a vital platform for showcasing the latest theoretical developments, methodological breakthroughs, and impactful real world applications.
We warmly invite authors from academia, industry, and research institutions to contribute to this vibrant exchange of ideas. Submissions may include original research articles, experimental studies, innovative projects, comprehensive surveys and industrial case studies that highlight significant progress in NLP and its emerging frontiers. Through these contributions, AdNLP 2026 aims to foster collaboration, inspire new directions, and advance the state of the art in Natural Language Computing.
Topics of interest include, but are not limited to, the following Foundations of Natural Language Processing
- Syntax, Parsing and Structured Prediction
- Morphology, Phonology and Lexical Semantics
- Semantics, Discourse and Pragmatics
- Linguistic Resources, Corpora and Benchmark Creation
- Knowledge Representation, Knowledge Graphs and Neuro Symbolic NLP
Machine Learning for NLP
- Deep Learning Architectures for NLP
- Large Language Models (LLMs): Training, Alignment and Evaluation
- Efficient NLP Models: Compression, Distillation, Quantization, Pruning
- Transfer Learning, Domain Adaptation and Low Resource NLP
- Continual, Lifelong and Online Learning for NLP
- Reinforcement Learning for Language Tasks
- Hybrid Statistical, Neural and Knowledge Based Methods
Data Centric and Synthetic Data NLP
- Synthetic Data Generation for NLP
- Data Quality, Filtering and Dataset Governance
- Automatic Dataset Creation for Low Resource Languages
- Contamination DetMultimodal and Speech Processing ection and Dataset Auditing
Generative and Interactive NLP
- Text Generation, Summarization and Controlled Generation
- Paraphrasing, Entailment and Natural Language Inference
- Dialogue Systems, Conversational AI and Chatbots
- Question Answering, Reasoning and Explainable NLP
- Narrative Understanding and Story Generation
- Retrieval Augmented Generation (RAG) and Knowledge Grounded Models
Reasoning, Planning and Advanced Capabilities
- Mathematical and Symbolic Reasoning
- Logical Inference and Formal Verification
- Multi Step Reasoning and Chain of Thought Models
- Planning, Tool Use and Function Calling Models
Long Context, Memory and Architecture Innovations
- Long Context Transformers and Efficient Attention
- Memory Augmented Language Models
- Document Level and Multi Document Reasoning
- Scalable and Distributed NLP Architectures
Multimodal and Speech Processing
- Vision Language Models (VLMs)
- Audio Language and Speech Language Models
- Speech Recognition, Synthesis and Spoken Language Understanding
- Video Language Understanding and Generation Multimodal Dialogue and Interactive Systems
Agentic and Autonomous Language Systems
- Agentic AI and Autonomous Language Agents
- Multi Agent Communication and Collaboration
- Tool Using Models and API Driven Language Systems
- Embodied AI and Robotics Language Interfaces
Responsible, Safe and Trustworthy NLP
- Bias, Fairness and Ethical NLP
- Safety, Hallucination Detection and Robustness
- Privacy Preserving NLP (Federated Learning, Differential Privacy)
- Security, Adversarial Attacks and Defenses
- Environmental Impact and Sustainable NLP
- AI Governance, Policy and Societal Impact
Evaluation, Benchmarking and Reproducibility
- Evaluation Metrics and Benchmark Design
- Meta Evaluation and Evaluation Reliability
- Human AI Comparative Evaluation
- Reproducibility, Transparency and Open Science
Applied and Domain Specific NLP
- Machine Translation and Cross Lingual NLP
- Information Extraction, Text Mining and Neural Search
- Biomedical, Clinical and Healthcare NLP
- Legal, Financial and Policy Driven NLP
- Scientific NLP and Research Automation
- NLP for Software Engineering, Code Understanding and Program Synthesis
- NLP for Education, Assessment and Learning Technologies
- NLP for Social Media, Misinformation and Digital Safety
- NLP for Climate Science, Sustainability and Environmental Modeling
Cognitive, Human Centered and Interdisciplinary NLP
- Cognitive Modeling and Psycholinguistics
- Brain Language Interfaces (EEG/fMRI + NLP)
- Human AI Collaboration and Co Creation
- Human in the Loop Learning and Annotation
- NLP for HCI and Interactive Systems
Paper Submission Authors are invited to submit papers through the conference Submission System by May 09, 2026. 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 Computer Science Conference Proceedings (H index 46) in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from AdNLP 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | May 09, 2026 | | Authors Notification | : | May 23, 2026 | | Final Manuscript Due | : | May 30, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to adnlp@sai2026.org |
