<2024-10th Digital Universe Colloquium>
TelBench: A Benchmark for Evaluating Telco-Specific Large Language Models
Speker: In-Ji Song (Researcher at SKT)
* Host: Hong, Jin-Hyuk
Date/Time: November 28, 2024 (Thurs) 16:00–17:30
Location: Oryong Hall(W1) Room 101
Language: Korean
Below is an abstract of the talk:
The telecommunications industry, characterized by its vast customer base and complex service offerings, necessitates a high level of domain expertise and proficiency in customer service center operations. Consequently, there is a growing demand for Large Language Models (LLMs) to augment the capabilities of customer service representatives. This presentation introduces a methodology for developing a specialized Telecommunications LLM (Telco LLM) designed to enhance the efficiency of customer service agents and promote consistency in service quality across representatives. We present the construction process of TelBench, a novel dataset created for performance evaluation of customer service expertise in the telecommunications domain. We also evaluate various LLMs and demonstrate the ability to benchmark both proprietary and open-source LLMs on predefined telecommunications related tasks, thereby establishing metrics that define telecommunications performance.
**Students interested in the lecture can attend even if they haven't registered, provided there are available seats in the classroom.
