کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

TELLM: Advancements in Knowledge Incorporation and Task-specific Enhancements of Large Language Models

نویسندگان :

Fatemeh Feizi¹ Amirhossein Hossein Nia² MohammadMahdi Hemmatyar³ Fatemeh Rahimi⁴ Farhoud Jafari Kaleibar⁵

1- ایرانسل 2- ایرانسل 3- ایرانسل 4- ایرانسل 5- ایرانسل

کلمات کلیدی :

Large Language Model،Deep Learning،Telecom،Question-answering

چکیده :

Customer service is crucial for any business to maintain good customer relationships and growth. However, addressing a wide variety of customer inquiries often requires deep domain expertise that may not be readily available. This paper presents TELLM, a customer service AI agent leveraging large language models to provide technical support for telecom companies. TELLM is trained using a knowledge base containing categorized technical solutions through dual-phase fine-tuning. It is further refined through reinforcement learning with feedback from subject matter experts. Evaluation on a real-world customer service dataset demonstrates TELLM outperforms prior approaches on automatic metrics and achieves high scores in human evaluation for response accuracy, clarity and effectiveness.

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