7th International Conference on Advanced Natural Language Processing (AdNLP 2026)

Name: 7th International Conference on Advanced Natural Language Processing (AdNLP 2026)
Start: 2026-06-20T10:00:00+11:00
End: 2026-06-20T11:00:00+11:00
Location: Sydney, Australia

Schedule

Sat Jun 20 2026 at 10:00 am to 11:00 am

UTC+11:00

Location

Sydney, Australia | Sydney, NS

7th International Conference on Advanced Natural Language Processing (AdNLP 2026)

June 20 ~ 21, 2026, Sydney, Australia

https://sai2026.org/adnlp/index

SCOPE

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

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 Det Multimodal and Speech Processing section 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 16, 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 issues of the following journals.