7^th International Conference on Natural Language Processing and Applications (NLPA 2026)

July 25 ~ 26, 2026, Toronto, Canada

7^th International Conference on Natural Language Processing and Applications (NLPA 2026) will provide an excellent international forum for sharing knowledge, exchanging ideas, and presenting the latest advances in the theory, methodology, and applications of Natural Language Processing (NLP). As language technologies continue to evolve through breakthroughs in large language models, multimodal systems, conversational AI, and knowledge driven applications, NLPA 2026 aims to highlight both foundational research and cutting edge innovations that are shaping the future of human language understanding.

The conference seeks significant contributions across all major areas of Natural Language Processing, spanning theoretical frameworks, computational models, linguistic analysis, machine learning approaches, and real world applications. NLPA 2026 brings together researchers, practitioners, and industry experts from around the world to foster collaboration, stimulate discussion, and explore emerging trends that are redefining the capabilities of modern language technologies. Contributions describing novel ideas, emerging directions, and transformative applications are especially encouraged. Papers that bridge NLP with other areas of Computer Science, Engineering, and Applied AI are also welcome.

Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works, and industrial experiences that describe significant advances in the areas of Natural Language Processing, Artificial Intelligence, Machine Learning, Speech Technologies, Multimodal Systems, and related applications.

Topics of interest include, but are not limited to, the following

Linguistics, Syntax and Semantics


• Phonology, Morphology and Lexical Semantics
  
• Syntax, Parsing and Grammatical Formalisms
  
• Semantic Processing, Compositional Semantics and Pragmatics
  
• Discourse Analysis, Coreference and Narrative Understanding
  
• Linguistic Resources, Corpora and Annotation Frameworks
  
• Ontologies, Knowledge Graphs and Semantic Representation
  
  Large Language Models (LLMs) and Foundation Models
  
  
• Pretraining, Fine Tuning and Instruction Tuning
  
• LLM Reasoning, Planning and Tool Use
  
• Retrieval Augmented Generation (RAG) and Memory Augmented LLMs
  
• Long Context Models, Compression and Efficient Attention
  
• LLM Safety, Alignment, Red Teaming and Hallucination Mitigation
  
• LLM Evaluation, Benchmarking and Robustness
  
• Multilingual, Cross Lingual and Low Resource LLMs
  
  Machine Learning for NLP
  
  
• Neural, Statistical and Hybrid NLP Methods
  
• Self Supervised and Representation Learning
  
• Continual, Lifelong and Online Learning for NLP
  
• Transfer Learning, Domain Adaptation and Cross Domain NLP
  
• Causal NLP and Causal Representation Learning
  
• Explainable, Trustworthy and Robust NLP
  
• Efficient NLP: Distillation, Quantization and Edge Deployment
  
  Natural Language Generation, Reasoning and Transformation
  
  
• Text Generation, Summarization and Paraphrasing
  
• Natural Language Inference, Entailment and Logical Reasoning
  
• Chain of Thought, Structured Reasoning and Symbolic Neural Integration
  
• Controlled Generation, Style Transfer and Text Simplification
  
• Data to Text, Knowledge to Text and Structured Generation
  
• Narrative Generation, Storytelling and Creative NLP
  
  Information Access, Retrieval and Knowledge Extraction
  
  
• Neural Information Retrieval (IR) and Dense Retrieval
  
• Hybrid Symbolic Neural Retrieval and Knowledge Augmented Models
  
• Information Extraction (IE), Event Extraction and Relation Extraction
  
• Text Mining, Topic Modeling and Document Understanding
  
• Question Answering (QA) and Reading Comprehension
  
• Fact Checking, Claim Verification and Misinformation Detection
  
• Document AI, OCR Free Models and Layout Aware Transformers
  
  Machine Translation and Multilingual NLP
  
  
• Neural Machine Translation (NMT)
  
• Cross Lingual Transfer and Multilingual Modeling
  
• Low Resource and Zero Shot Translation
  
• Speech to Text and Speech to Speech Translation
  
• Multimodal Translation Dialogue, Conversational AI and Language Agents
  
• Dialogue Systems and Conversational Agents
  
• Task Oriented Dialogue and Interactive Assistants
  
• Open Domain Chatbots and Safety in Dialogue
  
• Autonomous Language Agents and Multi Agent Communication
  
• Language Driven Tool Use and Planning Agents
  
• Emotion, Sentiment, Social NLP and Affective Dialogue
  
  Speech, Audio and Spoken Language Technologies
  
  
• Speech Recognition (ASR) and Speech Synthesis (TTS)
  
• Spoken Language Understanding (SLU)
  
• Prosody, Speaker Identification and Emotion in Speech
  
• Speech Language Multimodal Models
  
• End to End Speech to Speech Modeling
  
• Audio Language Grounding and Multimodal Speech Reasoning
  
  Multimodal NLP and Vision Language Models
  
  
• Vision Language Models (VLMs) and Multimodal Transformers
  
• Text Image, Text Video and Text Audio Understanding
  
• Multimodal Reasoning and Cross Modal Alignment
  
• Document AI, Layout Understanding and Multimodal OCR
  
• Multimodal Generation (Image/Video/Audio from Text)
  
• Embodied Language Models and Vision Language Action Systems
  
  Applied NLP and Domain Specific Language Technologies
  
  
• Biomedical NLP, Clinical Text Mining and Healthcare AI
  
• Legal NLP, Financial NLP and Scientific NLP
  
• NLP for Education, Assessment and Learning Analytics
  
• NLP for Social Media, Online Safety and Moderation
  
• NLP for E commerce, Personalization and Recommendation
  
• NLP for Scientific Discovery, Research Automation and Literature Mining
  
  NLP Infrastructure, Evaluation and Ethics
  
  
• NLP Datasets, Benchmarks and Evaluation Science
  
• Human in the Loop Evaluation and Cognitive Testing
  
• Data Quality, Bias Detection and Fairness in NLP
  
• Privacy Preserving NLP and Federated Language Models
  
• Efficient Training, Inference and Deployment
  
• Responsible NLP, Ethics, Governance and Societal Impact
  

Paper Submission

Authors are invited to submit papers through the conference Submission System by May 30, 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 in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from NLPA 2026, after further revisions, will be published in the special issue of the following journals.

• International Journal of Computer Science & Information Technology (IJCSIT) - INSPEC Indexed
  
• International Journal on Information Theory (IJIT)
  
• International Journal on Natural Language Computing (IJNLC)
  
• International Journal of Web & Semantic Technology (IJWesT)
  
• International Journal on Computational Science & Applications (IJCSA)
  
• Information Technology in Industry (ITII)
  

Important Dates

Co - Located Event

• 12^th International Conference on Image Processing and Pattern Recognition (IPPR 2026)
  
• 12^th International Conference on Software Engineering (SOENG 2026)
  
• 14^th International Conference of Security, Privacy and Trust Management (SPTM 2026)
  
• 15^th International conference on Parallel, Distributed Computing and Applications (IPDCA 2026)
  
• 12^th International Conference on Data Mining (DaMi 2026)
  
• 12^th International Conference on Artificial Intelligence and Soft Computing (AIS 2026)
  
• 13^th International Conference on Computer Science and Information Technology (CSIT 2026)
  
• 7^th International Conference on Advanced Machine Learning (AMLA 2026)
  
• 7^th International Conference on Big Data and Applications (BDAP 2026)
  

***** The invited talk proposals can be submitted to nlpa@csit2026.org