Unleashing the Power of Language: A Performance-based Case Study of Large Language Models

  • Unique Paper ID: 161549
  • Volume: 10
  • Issue: 4
  • PageNo: 592-600
  • Abstract:
  • Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) with their exceptional language understanding and generation capabilities. This research paper presents a comprehensive performance-based case study of LLMs to assess their effectiveness across various domains, identify their strengths and limitations, and explore the implications for future developments in NLP. The study includes an examination of LLMs' performance on benchmark datasets, encompassing natural language understanding (NLU) tasks such as sentiment analysis, named entity recognition, and text classification, as well as natural language generation (NLG) tasks like text summarization, dialogue generation, and story completion. Evaluation metrics such as accuracy, precision, recall, F1 score, and perplexity are employed to measure their performance. Additionally, the paper discusses the ethical considerations associated with LLMs, including biases, fairness, and privacy concerns, and explores potential challenges in deploying and utilizing these models effectively. By addressing these concerns and leveraging the potential of LLMs, this research aims to contribute to advancements in NLP and open up new possibilities across diverse domains.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{161549,
        author = {Manikandan and Dr. BVANSS Prabhakar Rao},
        title = {Unleashing the Power of Language: A Performance-based Case Study of Large Language Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {4},
        pages = {592-600},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161549},
        abstract = {Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) with their exceptional language understanding and generation capabilities. This research paper presents a comprehensive performance-based case study of LLMs to assess their effectiveness across various domains, identify their strengths and limitations, and explore the implications for future developments in NLP. The study includes an examination of LLMs' performance on benchmark datasets, encompassing natural language understanding (NLU) tasks such as sentiment analysis, named entity recognition, and text classification, as well as natural language generation (NLG) tasks like text summarization, dialogue generation, and story completion. Evaluation metrics such as accuracy, precision, recall, F1 score, and perplexity are employed to measure their performance. Additionally, the paper discusses the ethical considerations associated with LLMs, including biases, fairness, and privacy concerns, and explores potential challenges in deploying and utilizing these models effectively. By addressing these concerns and leveraging the potential of LLMs, this research aims to contribute to advancements in NLP and open up new possibilities across diverse domains.},
        keywords = {Large Language Models, language understanding, language generation, benchmark datasets, sentiment analysis, named entity recognition, text classification, dialogue generation, story completion, ethical considerations, biases, fairness, privacy concerns, future developments.},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 4
  • PageNo: 592-600

Unleashing the Power of Language: A Performance-based Case Study of Large Language Models

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