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صفحه اصلی
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سی و دومین کنفرانس بین المللی مهندسی برق
TELLM: Advancements in Knowledge Incorporation and Task-specific Enhancements of Large Language Models
نویسندگان :
Fatemeh Feizi
1
Amirhossein Hossein Nia
2
MohammadMahdi Hemmatyar
3
Fatemeh Rahimi
4
Farhoud Jafari Kaleibar
5
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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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.7.2
