Advancing Natural Language Processing: A Journey Through the Evolution of Language Models
- DOI
- 10.2991/978-94-6463-787-8_32How to use a DOI?
- Keywords
- Natural Language Processing (NLP); Transformers; RNNs; CNNs; MLPs; LSTMs
- Abstract
Natural language processing (NLP) has come a long way from a basic rule-based system to the sophisticated AI models we use today. The system used to adhere to rigid rules, which worked well for simple tasks but had trouble with the complexity of real-world language. The introduction of machine learning, including neural networks like MLPs, CNNs, RNNs, brought some huge improvements, but the real ground breaker came in 2017 with the transformer model. Transformers, with their ability to process text parallel and focus on key parts of the sentences, which completely transformed NLP. Today, models like BERT and GPT are at the soul of applications like chatbots, translations and summarization. This paper looks at the journey of language models, the breakthroughs in the field, the challenges that remain, and the interesting future possibilities, including combining text with other forms of data.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Akanksha Bisht AU - Aditi Gupta AU - Aarsh Mall AU - Nidhi Rana PY - 2025 DA - 2025/07/17 TI - Advancing Natural Language Processing: A Journey Through the Evolution of Language Models BT - Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025) PB - Atlantis Press SP - 397 EP - 415 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-787-8_32 DO - 10.2991/978-94-6463-787-8_32 ID - Bisht2025 ER -