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Seojin Lee

3 accepted papers

2024

TelBench: A Benchmark for Evaluating Telco-Specific Large Language Models

EMNLP 2024industry

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 capabil…

Cited by 0SourcePDFScholar
2023

What, When, and How to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue

ACL 2023industry

This paper presents a method for building a personalized open-domain dialogue system to address the WWH (WHAT, WHEN, and HOW) problem for natural response generation in a commercial setting, where personalized dialogue responses are heavily interleaved with casual response turns. The proposed approa…

Cited by 12SourcePDFScholar
2021

An Evaluation Dataset and Strategy for Building Robust Multi-turn Response Selection Model

EMNLP 2021main

Multi-turn response selection models have recently shown comparable performance to humans in several benchmark datasets. However, in the real environment, these models often have weaknesses, such as making incorrect predictions based heavily on superficial patterns without a comprehensive understand…