1 citations · 2 across the 4 of their papers we have counts for
4 papers
Korean Canonical Legal Benchmark: Toward Knowledge-Independent Evaluation of LLMs' Legal Reasoning Capabilities
Hongseok Oh, Wonseok Hwang, Kyoung-Woon On
We introduce the Korean Canonical Legal Benchmark (KCL), a benchmark designed to assess language models' legal reasoning capabilities independently of domain-specific knowledge. KC…
LRAGE: Legal Retrieval Augmented Generation Evaluation Tool
Minhu Park, Hongseok Oh, Eunkyung Choi +1
Recently, building retrieval-augmented generation (RAG) systems to enhance the capability of large language models (LLMs) has become a common practice. Especially in the legal doma…
Taxation Perspectives from Large Language Models: A Case Study on Additional Tax Penalties
Eunkyung Choi, Youngjin Suh, Siun Lee +5
How capable are large language models (LLMs) in the domain of taxation? Although numerous studies have explored the legal domain, research dedicated to taxation remains scarce. Mor…
Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models
Yeeun Kim, Young Rok Choi, Eunkyung Choi +3
Large language models (LLMs) have demonstrated remarkable performance in the legal domain, with GPT-4 even passing the Uniform Bar Exam in the U.S. However their efficacy remains l…