7th International Conference on NLP & Big Data (NLPD 2026)

Thu, 16 Jul, 2026 at 09:00 am to Fri, 17 Jul, 2026 at 06:00 pm UTC+01:00

London, United Kingdom | London

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Publisher/Hostleo farina
7th International Conference on NLP & Big Data (NLPD 2026)
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7th International Conference on NLP & Big Data (NLPD 2026)

 

July 16 ~ 17, 2026, London, United Kingdom

 

https://nlpd2026.org/index

 

Scope

 

The 7th International Conference on NLP and Big Data (NLPD 2026) serves as a premier global forum for researchers, practitioners, and industry experts to exchange cutting edge knowledge and advances in Natural Language Processing, Large Language Models, and Big Data technologies. As the fields of NLP and data driven AI continue to evolve at unprecedented speed, NLPD 2026 aims to bring together diverse perspectives that push the boundaries of theory, methodology, and real world applications.

 

The conference welcomes high quality contributions that explore foundational models, innovative algorithms, scalable systems, and transformative applications across domains. NLPD 2026 encourages submissions that address emerging challenges, propose novel solutions, or offer deep insights into the rapidly expanding landscape of intelligent language technologies and big data analytics.

 

Authors are invited to contribute original research articles, case studies, survey papers, and industrial experiences that demonstrate significant advances in the areas listed below. Submissions are not limited to these topics, and interdisciplinary work is strongly encouraged.

 

Topics of interest

 

Large Language Models and Foundation Models

 

  • Training, fine tuning, and alignment of LLMs
  • Instruction following, preference optimization, and RLHF
  • Constitutional AI and self alignment
  • Mechanistic interpretability and model internals
  • Retrieval Augmented Generation (RAG) and knowledge augmented LLMs
  • Long context modeling, memory augmented architectures, and recurrent LLMs
  • Efficient LLMs: compression, distillation, quantization, pruning
  • Multilingual, cross lingual, and low resource LLMs
  • Evaluation of LLMs: behavioral, safety, robustness, and benchmarking
  • LLM as a judge and automated evaluation frameworks

 

 NLP Agents, Reasoning and Autonomous Systems

 

  • LLM based agents and tool use
  • Multi agent systems, emergent behavior, and collective intelligence
  • Planning, reasoning, and multi step problem solving
  • Workflow synthesis, tool orchestration, and agentic pipelines
  • Social simulation using LLM agents
  • Embodied AI and language conditioned robotics
  • Simulation environments for agent evaluation

 

 Core Natural Language Processing

 

  • Syntax, semantics, pragmatics, and discourse
  • Information extraction, information retrieval, and text mining
  • Question answering, machine reading, and knowledge intensive NLP
  • Dialogue systems, conversational AI, and speech language integration
  • Argumentation mining, stance detection, and opinion analysis
  • Corpus linguistics and large scale corpus analysis
  • Causal inference for NLP

 

 Multimodal and Generative AI

 

  • Vision language, audio language, and video language models
  • Cross modal retrieval, grounding, and alignment
  • Generative models for text, image, audio, and video
  • Narrative generation, creative AI, and story understanding
  • Spatial, 3D, and embodied multimodal models

 

 Big Data, Knowledge Systems and Web Scale Intelligence

 

  • Big data analytics and scalable machine learning
  • Knowledge graphs, semantic web, and linked data
  • Ontologies and semantic processing
  • Web and social media analytics
  • Data governance, provenance, and dataset auditing
  • Data contamination detection and dataset filtering
  • Synthetic data generation and data augmentation
  • Data centric AI and dataset quality optimization

 

 Trustworthy, Safe and Responsible AI

 

  • Fairness, accountability, transparency, and ethics in NLP
  • Bias detection and mitigation in language models
  • Privacy preserving NLP (federated learning, differential privacy)
  • Adversarial attacks, robustness, and red teaming
  • Hallucination detection and mitigation
  • Safety evaluation and secure deployment of LLMs
  • Governance, auditing, and regulatory compliance for AI systems
  • Eco responsible AI and energy efficient NLP

 

 Applied NLP and Domain Specific Intelligence

 

  • NLP for healthcare, biomedical text, and scientific discovery
  • NLP for law, finance, policy, and government
  • NLP for education, tutoring, and assessment
  • Computational social science using NLP
  • NLP for climate, sustainability, and social good
  • Domain adapted and specialized LLMs

 

 NLP for Emerging Computing Paradigms

 

  • Edge, mobile, and embedded NLP systems
  • Personalized and adaptive NLP systems
  • Continual learning and lifelong adaptation
  • NLP for IoT and smart environments
  • NLP for robotics and human robot interaction
  • NLP in AR/VR and spatial computing

 

 Code, Math and Scientific NLP

 

  • Code LLMs, program synthesis, and natural language for programming
  • Automated software engineering with LLM agents
  • Mathematical reasoning and MathNLP
  • NLP for scientific literature, discovery, and hypothesis generation
  • Knowledge editing, model patching, and fact updating
  • Neuro symbolic reasoning and hybrid systems

 

 Cognitive Modeling, NeuroAI and Human Centered NLP

 

  • Cognitive modeling with LLMs
  • Brain language alignment and neural decoding
  • Human AI collaboration and co creativity
  • Social grounding, cultural adaptation, and anthropological NLP
  • Human in the loop NLP and interactive learning

 

 Evaluation, Methodology and Reproducibility

 

  • Benchmark creation and dataset design
  • Reproducibility, transparency, and open science
  • Error analysis, interpretability, and explainability
  • Meta evaluation and evaluation of evaluators
  • Automated benchmark generation

 

 Systems, Infrastructure and Optimization

 

  • Distributed training and inference for large models
  • High performance computing for NLP and big data
  • Scalable architectures for real time NLP applications
  • Model serving, deployment, and monitoring at scale
  • Energy efficient and carbon aware model training

 

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 NLPD 2026, after further revisions, will be published in the special issue of the following journals

 

·      International Journal on Natural Language Computing (IJNLC)

·      International Journal of Web & Semantic Technology (IJWesT) - IS Indexed

·      International Journal of Ubiquitous Computing (IJU)

·      International Journal of Data Mining & Knowledge Management Process (IJDKP)

·      The International Journal of Ambient Systems and Applications (IJASA)

·      International Journal of Grid Computing & Applications (IJGCA)

 

Important Dates

 

·      Submission Deadline : May 16, 2026

·      Authors Notification : June 20, 2026

·      Registration & Camera-Ready Paper Due : June 27, 2026

 

Contact Us

 

Here's where you can reach us : [email protected] or [email protected]

 

Submission URL: https://cseit2026.org/submission/index.php


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