@article{ART003305933},
author={Gyuhyeong Kim and Yunhyeok Do and Joonhyeon Song and Ziyang Liu},
title={RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={2},
pages={51-64},
doi={10.9708/jksci.2026.31.02.051}
TY - JOUR
AU - Gyuhyeong Kim
AU - Yunhyeok Do
AU - Joonhyeon Song
AU - Ziyang Liu
TI - RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 2
PB - The Korean Society Of Computer And Information
SP - 51
EP - 64
SN - 1598-849X
AB - Hallucination and outdated knowledge in large language models critically undermine their reliability and applicability in specialized domains such as law and medicine, where factual accuracy is essential. While Retrieval-Augmented Generation (RAG) has been proposed as a mitigation strategy, its effectiveness in the legal domain is often hindered by lexical mismatches, which impede the accurate retrieval of highly relevant external knowledge. Although several studies have explored query formulation–based approaches to address this issue, additional training costs and hallucination during the retrieval phase remain persistent challenges.
In this paper, we propose RAR-Agent (Rationale-Augmented Retrieval Agent) to overcome these limitations.
RAR-Agent employs a Chain-of-Thought and Rationale-based query formulation technique, combined with a Reciprocal Rank Fusion and Reranker-based filtering mechanism, to alleviate lexical mismatch problems and effectively suppress hallucination during retrieval. Furthermore, to precisely evaluate the agent’s factual accuracy, we constructed the KL-BQA (Korean Legal Binary Question-Answering) benchmark. The proposed model achieved superior performance on both the KL-BQA and KL-RQA benchmarks.
KW - AI Agent;Legal Agent;RAG;Legal QA;Query Formulation;Hybrid Retrieval
DO - 10.9708/jksci.2026.31.02.051
ER -
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song and Ziyang Liu. (2026). RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering. Journal of The Korea Society of Computer and Information, 31(2), 51-64.
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song and Ziyang Liu. 2026, "RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering", Journal of The Korea Society of Computer and Information, vol.31, no.2 pp.51-64. Available from: doi:10.9708/jksci.2026.31.02.051
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song, Ziyang Liu "RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering" Journal of The Korea Society of Computer and Information 31.2 pp.51-64 (2026) : 51.
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song, Ziyang Liu. RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering. 2026; 31(2), 51-64. Available from: doi:10.9708/jksci.2026.31.02.051
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song and Ziyang Liu. "RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering" Journal of The Korea Society of Computer and Information 31, no.2 (2026) : 51-64.doi: 10.9708/jksci.2026.31.02.051
Gyuhyeong Kim; Yunhyeok Do; Joonhyeon Song; Ziyang Liu. RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering. Journal of The Korea Society of Computer and Information, 31(2), 51-64. doi: 10.9708/jksci.2026.31.02.051
Gyuhyeong Kim; Yunhyeok Do; Joonhyeon Song; Ziyang Liu. RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering. Journal of The Korea Society of Computer and Information. 2026; 31(2) 51-64. doi: 10.9708/jksci.2026.31.02.051
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song, Ziyang Liu. RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering. 2026; 31(2), 51-64. Available from: doi:10.9708/jksci.2026.31.02.051
Gyuhyeong Kim, Yunhyeok Do, Joonhyeon Song and Ziyang Liu. "RAR-Agent: A Rationale-Augmented Retrieval Framework for Legal Question Answering" Journal of The Korea Society of Computer and Information 31, no.2 (2026) : 51-64.doi: 10.9708/jksci.2026.31.02.051
