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Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing

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arxiv 2304.02017 v14 pith:XXMXHF7M submitted 2023-03-27 cs.CL

Walid Hariri This is my paper · ORCID
classification cs.CL
keywords languageapplicationschatgptlimitationsnaturaladvantagesartificialcomprehensive
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Large language models, pivotal in artificial intelligence, find diverse applications. ChatGPT (Chat Generative Pre-trained Transformer), an OpenAI creation, stands out as a widely adopted, powerful tool. It excels in chatbots, content generation, language translation, recommendations, and medical applications, due to its ability to generate human-like responses, comprehend natural language, and adapt contextually. Its versatility and accuracy make it a potent force in natural language processing (NLP). Despite successes, ChatGPT has limitations, including biased responses and potential reinforcement of harmful language patterns. This article offers a comprehensive overview of ChatGPT, detailing its applications, advantages, and limitations. It also describes the main advancements from GPT-3 to GPT-4 Omni, comparing them with other LLMs like LLaMA 3, Gemini and Deepseek. The paper underscores the ethical imperative when utilizing this robust tool in practical settings. Furthermore, it contributes to ongoing discussions on artificial intelligence's impact on vision and NLP domains, providing insights into prompt engineering techniques.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SwiftSpec: Ultra-Low Latency LLM Decoding by Scaling Asynchronous Speculative Decoding

    cs.DC 2025-06 conditional novelty 6.0 of 10

    SwiftSpec uses asynchronous, disaggregated speculative decoding with parallel tree generation and fused kernels to speed up LLM decoding by 1.75x on average over baselines, reaching 348 tokens/s for Llama3-70B on 8 H800 GPUs.

  2. An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3

    cs.CL 2025-05 conditional novelty 4.0 of 10

    LLMs can produce fluent movie reviews that readers often mistake for human-written ones, but the models differ in emotional balance and depth.

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