Cited by Enhancing Generative AI Chatbot Accuracy Using Knowledge Graph

B. Sathish Babu,

Mithula Umakanth,

P. Bhanumathi

et al.

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 413 - 430

Published: Feb. 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.

Language: Английский

Citations

Conscious Leather Design Academy DOI

Roberto Liberti,

Luigi Chierchia, Valentina Alfieri

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Assessing Fine-Tuning Efficacy in LLMs: A Case Study with Learning Guidance Chatbots DOI

Rabia Bayraktar,

Batuhan Sarıtürk,

Merve Elmas Erdem

et al.

International Journal of Innovative Science and Research Technology (IJISRT), Journal Year: 2024, Volume and Issue: unknown, P. 2461 - 2471

Published: June 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.

Language: Английский

Citations

Evaluation of the Effectiveness of Prompts and Generative AI Responses DOI

Ajay Bandi,

Ruida Zeng

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 56 - 69

Published: Dec. 21, 2024

Language: Английский

Citations

Enhancing Generative AI Chatbot Accuracy Using Knowledge Graph DOI

Ajay Bandi,

Jameer Babu,

Ruida Zeng

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 157 - 167

Published: Oct. 18, 2024

Language: Английский

Citations