Papers by SeongTae Hong
KoCommonGEN v2: A Benchmark for Navigating Korean Commonsense Reasoning Challenges in Large Language Models (2024.findings-acl)
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| Challenge: | Language models are striving to grasp commonsense reasoning, but they are lacking in Korean commons- ense benchmarks. |
| Approach: | They present a fine-grained benchmark dataset focused on Korean commonsense reasoning that includes multiple-choice questions across seven error categories. |
| Outcome: | The proposed datasets show that LLMs struggle with Korean commonsense reasoning . human accuracy benchmarked at approximately 85%, while GPT-4’s performance lags at about 74%, and other LLM models demonstrate an average accuracy of around 42%. |
Translation of Multifaceted Data without Re-Training of Machine Translation Systems (2024.findings-emnlp)
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| Challenge: | a novel MT pipeline that considers the intra-data relation is proposed . previous MT systems have demonstrated relatively low performance, making them hardly utilized as another data source. |
| Approach: | They propose a new MT pipeline that considers the intra-data relation . they propose CS and IT to enhance the intra data relation based on a data point . |
| Outcome: | The proposed pipeline improves translation quality and training data compared with the existing approach . it yields better training data and better translation quality than previous approaches . |