Papers by Seokyoung Hong

2 papers
TelBench: A Benchmark for Evaluating Telco-Specific Large Language Models (2024.emnlp-industry)

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Challenge: a growing demand for Large Language Models (LLMs) is requiring specialized models to augment customer service agents' skills.
Approach: They propose a methodology for developing a specialized Telecommunications LLM . they use a dataset to evaluate customer service expertise in the telecommunications domain .
Outcome: The proposed model improves the efficiency of customer service agents and reduces response times.
TelAgentBench: A Multi-faceted Benchmark for Evaluating LLM-based Agents in Telecommunications (2025.emnlp-industry)

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Challenge: Large Language Models (LLMs) are becoming powerful agentic systems . generic benchmarks fail to assess realistic, non-English performance .
Approach: They propose to evaluate five core agentic capabilities: Reasoning, Planning, Action (tool-use), Retrieval-Augmented Generation, and Instruction Following.
Outcome: The evaluations reveal significant performance disparities between models that employ explicit reasoning and those that do not.

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