Special Session #15

Natural Language Processing, Artificial Intelligence and Computation

 

Chair:

Prof. Mohammad Nadeem, Department of Computer Science, Aligarh Muslim University, Aligarh, India; e-mail: mnadeem.cs@amu.ac.in

Co-Chair:

Prof. Shahab Saquib Sohail, School of Computing Science and Engineering, VIT Bhopal University, Shore, MP, 466114, India; e-mail: shahabsaquibsohail@vitbhopal.ac.in


Computation, information sciences and their related technologies are concerned with the collection, classification, storage, retrieval and dissemination of information, and large language models (LLMs) like the ones used in natural language processing (NLP) are the products of progresses in information sciences. LLMs, as categories of foundation and optimization models that are trained on voluminous data, enable the understanding and generating of natural language along with other kinds of content so that a broad range of tasks can be carried out. Besides making generative artificial intelligence (AI) evident in public, LLMs orient users toward utilizing and benefiting from AI in different operations, functions, uses and cases. With these capabilities and increasing accessibility options, they represent a breakthrough in natural language processing and AI, LLMs have been configured to comprehend and generate a text like a human in different forms depending on the big data employed to train them. Thus, code generation tasks, answering questions, summarizing texts, translations and making contextually related responses have become possible, being in continual progress and development.

The aim of our special session is to present and discuss both opportunities, challenges and limitations regarding NLP, LLMs, generative AI tools and other related means by taking into account different language structures, morphologies, syntaxes and attributes along with different transitions across languages. Through these means, we intend to find out ways to enhance LLMs and other means for text analytics, linguistic, computational and information systems research applications.

The topics include but are not limited to:

  • Decoding generative AI, taxonomy, challenges, and future visions
  • Nature inspired optimization algorithms
  • Machine learning based predictive modeling
  • Automatic morphological analysis of languages
  • Control and informatics
  • Direct speech to speech translation
  • Language-machine translation and applications
  • Artificial Intelligence and image processing
  • Data format
  • Computational linguistics
  • Computational morphology
  • Morphological processing
  • Global Wordnet
  • Challenges of language and speech processing
  • Semantic similarity-based evaluations
  • Large language models (LLM) and applications
  • Logic of languages for natural language processing (NLP)
  • Artificial Intelligence Applications
  • Deep learning method and/or language database
  • Generative AI for language processes
  • Electronic corpus studies for languages
  • Web-based annotation systems
  • Intelligent techniques and applications
  • Computational intelligence
  • Recommender systems and classification
  • Rule-based and / or vector analyses