7th International Conference on NLP & Information Retrieval (NLPI 2026)

April 25 ~ 26, 2026, Copenhagen, Denmark

https://csitec2026.org/nlpi/index

Scope

As NLP and IR continue to transform communication, knowledge access, and intelligent systems, NLPI 2026 aims to bring together researchers, practitioners, and innovators to exchange ideas, explore emerging challenges, and shape the future of language centric AI. We welcome original, unpublished work that advances theory, algorithms, systems, and applications. All submissions will undergo rigorous peer review, and accepted papers will be included in the conference proceedings.

NLPI 2026 covers a broad range of topics in NLP, IR, and AI driven language technologies. We especially encourage submissions that address modern challenges such as large language models, retrieval augmented generation, multimodal systems, and responsible AI.

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

Core NLP Tasks & Linguistic Foundations

• Tokenization, POS tagging, chunking, and shallow parsing
• Parsing, grammatical formalisms, and syntactic analysis
• Lexical semantics and semantic role labeling
• Discourse, pragmatics, and dialogue structure
• Phonology, morphology, and linguistic theory
• Linguistic resources, corpora, and annotation methodologies

Large Language Models & Advanced NLP

• Foundation models and large language models (LLMs)
• Prompt engineering, fine tuning, and instruction following
• Hallucination detection and mitigation
• Multilingual, cross lingual, and low resource NLP
• Efficient NLP: compression, distillation, and acceleration

Information Retrieval & Search Technologies

• Classical and neural IR models
• Retrieval augmented generation (RAG)
• Contextual, personalized, and interactive IR
• Evaluation of IR systems and relevance feedback
• Decentralized and federated search
• Social, multimedia, and multimodal IR
• Web scale search, ranking, and indexing

Machine Learning for NLP & IR

• Deep learning architectures for NLP and IR
• Graph neural networks for text and knowledge graphs
• Statistical and knowledge based methods
• Representation learning for text and documents
• Contrastive learning and self supervised methods
• Online, continual, and lifelong learning

Knowledge Representation & Reasoning

• Ontologies, taxonomies, and semantic web
• Knowledge graph construction and completion
• Decentralized knowledge representation
• Reasoning over text, graphs, and multimodal data
• Hybrid neuro symbolic approaches

Generation, Summarization & Language Understanding

• Text generation, paraphrasing, and entailment
• Abstractive and extractive summarization
• Natural language inference (NLI)
• Controlled, safe, and ethical text generation
• Style transfer, simplification, and narrative generation

Dialogue, Conversational AI & Speech

• Dialogue systems and conversational agents
• Task oriented and open domain dialogue
• Spoken language understanding and dialogue management
• Speech recognition, synthesis, and voice conversion
• Multimodal conversational AI

Information Extraction & Text Mining

• Named entity recognition, relation extraction, event extraction
• Topic modeling, tracking, and subject indexing
• Text mining for scientific, legal, and biomedical domains
• Event and anomaly detection
• Trend analysis and large scale text analytics

Sentiment, Social Media & Affective Computing

• Sentiment analysis and opinion mining
• Emotion, personality, and behavioral signal detection
• NLP for social media, misinformation, and online safety
• Computational social science and social network analysis

Multimodal & Cross Domain NLP

• Vision language models (VLMs)
• Audio text, video text, and multimodal fusion
• Multimodal retrieval and generation
• Cross domain and cross modal transfer

Machine Translation & Multilingual Technologies

• Neural machine translation (NMT)
• Low resource and unsupervised MT
• Evaluation of MT quality and bias
• Speech to speech and multimodal translation

Ethics, Safety & Responsible AI

• Bias, fairness, and inclusivity in NLP and IR
• Privacy preserving NLP and federated learning
• Safety, robustness, and adversarial attacks
• Ethical considerations in language technologies
• Transparency, explainability, and model interpretability

Visualization, Interaction & Human Centered NLP

• Visualization of NLP and IR results
• Human AI collaboration and interactive NLP tools
• Explainable interfaces for search and language models
• User centered evaluation of NLP systems

Paper Submission

Authors are invited to submit papers through the conference Submission System by February 14, 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 NLPI 2026, after further revisions, will be published in the special issue of the following journal.

• International Journal on Natural Language Computing (IJNLC)
• International Journal of Web & Semantic Technology (IJWesT)
• International Journal of Database Management Systems (IJDMS)

Important Dates

• Submission Deadline: February 14, 2026
• Authors Notification: March 14, 2026
• Registration & camera – Ready Paper Due: March 21, 2026

Contact Us

Here’s where you can reach us : [email protected] (or) [email protected]

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