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Title:
A Comprehensive Overview of Large Language Models
Publish Date:
11 April 2024
Abstract:
These works encompass diverse topics such as architectural innovations, better training strategies, context length improvements, fine-tuning, multi-modal LLMs, robotics, datasets, benchmarking, efficiency, and more.
Considering the rapidly emerging plethora of literature on LLMs, it is imperative that the research community is able to benefit from a concise yet comprehensive overview of the recent developments in this field. This article provides an overview of the existing literature on a broad range of LLM-related concepts. Comprehensive overview of LLMs discusses relevant background concepts along with covering the advanced topics at the frontier of research in LLMs. This review article is intended to not only provide a systematic survey but also a quick comprehensive reference for the researchers and practitioners to draw insights from extensive informative summaries of the existing works to advance the LLM research. Keywords: Large Language Models, LLMs, chatGPT, Augmented LLMs, Multimodal LLMs, LLM training, LLM Benchmarking
Tags:
LLM, NLP
Review:
Dennis Kuriakose
Date:
26 August 2024
Review:
The paper summarises significant findings of LLMs in the existing literature and provides a detailed analysis of the;
Design aspects, including architectures, datasets, and training pipelines. Crucial architectural components and training strategies employed by different LLMs.
Discusses the performance differences of LLMs in zero-shot and few-shot settings,
Explores the impact of fine-tuning
Compares supervised and generalized models and encoder vs. decoder vs. encoder-decoder architectures.
A comprehensive review of multi-modal LLMs, retrieval augmented LLMs, LLMspowered agents
Efficient LLMs,
Datasets & Evaluation Metrics
LLM applications
Current challenges & future direction of research
All of this is referenced against the relevant research paper so the prior literature is directly accessible.
This paper is anticipated to serve as a valuable resource for researchers, offering insights into the recent advancements in LLMs and providing fundamental concepts and details to develop better LLMs.
The table below summarises all the key topics in a tree form.
Technology Posts
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