This comprehensive survey provides an in-depth analysis of modern LLMs, with a systematic comparison of cutting-edge proprietary and open-source architectures including DeepSeek, GPT-4, Gemini, LLaMA, and Claude.
Comparison of GPT-4, BERT (bidirectional encoder representations from transformers), Gemini, and DeepSeek large language models (LLM), focusing on architectures, training methodologies, and real-world applications reveals GPT-4 excels in natural language generation and complex reasoning, supporting up to 128K tokens wi...
Kavish Sanghvi, Aparna S. Sharma, Surbhi Hooda· Computer Science and Informa...· 0 citations
This survey reviews the evolution of language models from early statistical approaches to modern Transformer-based architectures and summarizes key developments, including attention mechanisms, scaling laws, alignment techniques, and efficient inference methods.
P. Peykani, V. Charles, A. Emrouznejad et al.· Archives of Computational Me...· 0 citations
This tutorial provides a comprehensive, end-to-end view of LLM interpretability, transitioning from microscopic neural analysis to macroscopic application and deployment, and explores how these interpretability paradigms scale and inspire the design of frontier architectures, agentic systems, and thinking models.
Wei Zhang, Zheng-Fu He, Lu-Lu Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
This survey aims to systematically address resource efficiency challenges in Large Language Models by reviewing a broad spectrum of techniques designed to enhance the resource efficiency of LLMs, and introduces a nuanced categorization of resource efficiency techniques by their specific resource types.
Two novel contributions are introduced: CodeEval and CodeQual, an open-source execution framework that provides researchers with a ready-to-use evaluation pipeline for evaluating and improving LLMs in software engineering contexts, encompassing both functional correctness assessment and subjective code quality evaluati...
Large Language Models (LLMs) have emerged as a transformative paradigm in Natural Language Processing (NLP), significantly advancing the capabilities of machines in understanding, generating, and reasoning with human language. Built upon transformer-based architectures and trained on massive datasets, LLMs have demonst...
Rampy, Anjana Kumari, Ranjit Singh· International journal of re...· 0 citations
