Evaluation of the Effectiveness of Prompts and Generative AI Responses DOI
Ajay Bandi,

Ruida Zeng

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 56 - 69

Опубликована: Дек. 21, 2024

Язык: Английский

Conscious Leather Design Academy DOI

Roberto Liberti,

Luigi Chierchia, Valentina Alfieri

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Generative Artificial Intelligence DOI
B. Sathish Babu,

Mithula Umakanth,

P. Bhanumathi

и другие.

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 413 - 430

Опубликована: Фев. 28, 2025

Generative Artificial Intelligence (AI) is a transformative force reshaping businesses. Advanced technology models, such as GPT-4, can produce content in various forms, from text to music, fundamentally changing many industries. The benefits are vast: personalized for enhanced customer experiences, improved virtual assistants, fostering creativity product design and generation, streamlining operations by automating routine tasks optimizing supply chains. While AI offers advanced analytics scenario simulations data-driven decision-making, businesses must be prepared address challenges. These challenges include ethical considerations, privacy concerns, regulatory compliance, the need skilled personnel. It crucial proactively these fully harness power of drive growth, efficiency, innovation. Using startups will game-changer contributing creative innovative solutions aspects business.

Язык: Английский

Процитировано

0

Assessing Fine-Tuning Efficacy in LLMs: A Case Study with Learning Guidance Chatbots DOI Open Access
Rabia Bayraktar,

Batuhan Sarıtürk,

Merve Elmas Erdem

и другие.

International Journal of Innovative Science and Research Technology (IJISRT), Год журнала: 2024, Номер unknown, С. 2461 - 2471

Опубликована: Июнь 10, 2024

Training and accurately evaluating task- specific chatbots is an important research area for Large Language Models (LLMs). These models can be developed general purposes with the ability to handle multiple tasks, or fine-tuned applications such as education customer support. In this study, Mistral 7B, Llama-2 Phi-2 are utilized which have proven success on various benchmarks, including question answering. The were using QLoRa limited information gathered from course catalogs. evaluated metrics, responses GPT-4 taken ground truth. experiments revealed that slightly outperformed achieving scores of 0.012 BLEU, 0.184 METEOR, 0.873 BERT. Considering evaluation metrics obtained, strengths weaknesses known LLM models, amount data required fine-tuning, effect fine-tuning method model performance discussed.

Язык: Английский

Процитировано

1

Enhancing Generative AI Chatbot Accuracy Using Knowledge Graph DOI
Ajay Bandi,

Jameer Babu,

Ruida Zeng

и другие.

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 157 - 167

Опубликована: Окт. 18, 2024

Язык: Английский

Процитировано

0

Evaluation of the Effectiveness of Prompts and Generative AI Responses DOI
Ajay Bandi,

Ruida Zeng

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 56 - 69

Опубликована: Дек. 21, 2024

Язык: Английский

Процитировано

0