Papers by Sereimony Sek
TelBench: A Benchmark for Evaluating Telco-Specific Large Language Models (2024.emnlp-industry)
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Sunwoo Lee, Dhammiko Arya, Seung-Mo Cho, Gyoung-eun Han, Seokyoung Hong, Wonbeom Jang, Seojin Lee, Sohee Park, Sereimony Sek, Injee Song, Sungbin Yoon, Eric Davis
| 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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Sunwoo Lee, Daseong Jang, Dhammiko Arya, Gyoung-eun Han, Injee Song, SaeRom Kim, Sangjin Kim, Seojin Lee, Seokyoung Hong, Sereimony Sek, Seung-Mo Cho, Sohee Park, Sungbin Yoon, Wonbeom Jang, Eric Davis
| 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. |