International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 3 (May-June 2026) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 3
May-June 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

A Comprehensive Review of Large Language Models: Architecture, Types, Challenges, and Future Directions

Author(s) Ms. Manisha Rajput, Ms. Kulwinder Kaur
Country India
Abstract “LLM play a big role are they how generate AI is improving today.” Their success is highly attributed to the Transformer architecture, which uses self-attention mechanisms and large-scale training corpora to model complex linguistic dependencies and long-range relationships. This review synthesizes the theoretical foundations that underpin LLM design, emphasizing the role of self-attention in contextual understanding and outlining the structural distinctions between encoder–decoder systems and modern decoder-only generative models. The paper further investigates practical applications of LLMs across domains such as content production, conversational systems, decision support, and specialized analytical workflows. Despite their capabilities, LLMs face persistent challenges including hallucination, context limitations, computational demands, and issues of trustworthiness. People are concerned that the system might be unfair or biased, fairness, transparency, and interpretability continue to influence are they deployment take decisions. Looking ahead, the field is shaped by emerging trends including multimodal expansion, efficiency-oriented model compression, retrieval-augmented techniques for factual grounding, and the development of agentic systems capable of autonomous task execution. While LLMs hold transformative potential, realizing their long-term societal benefits requires continued progress toward more reliable, efficient, and ethically aligned systems.
Keywords AI language models, Transformers, attention, model types, errors, bias, retrieval methods, multimodal AI, AI agents
Field Computer Applications
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-05
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62263
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 3Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 2

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals