5 papers
Why Do Multilingual Reasoning Gaps Emerge in Reasoning Language Models?
Deokhyung Kang, Seonjeong Hwang, Daehui Kim +2
Reasoning language models (RLMs) achieve strong performance on complex reasoning tasks, yet they still exhibit a multilingual reasoning gap, performing better in high-resource lang…
KoBLEX: Open Legal Question Answering with Multi-hop Reasoning
Jihyung Lee, Daehui Kim, Seonjeong Hwang +2
Large Language Models (LLM) have achieved remarkable performances in general domains and are now extending into the expert domain of law. Several benchmarks have been proposed to e…
GuRE:Generative Query REwriter for Legal Passage Retrieval
Daehee Kim, Deokhyung Kang, Jonghwi Kim +2
Legal Passage Retrieval (LPR) systems are crucial as they help practitioners save time when drafting legal arguments. However, it remains an underexplored avenue. One primary reaso…
Exploring Iterative Controllable Summarization with Large Language Models
Sangwon Ryu, Heejin Do, Daehee Kim +5
Large language models (LLMs) have demonstrated remarkable performance in abstractive summarization tasks. However, their ability to precisely control summary attributes (e.g., leng…
Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Model
Daehee Kim, Deokhyung Kang, Sangwon Ryu +1
Knowledge Graph-to-Text (G2T) generation involves verbalizing structured knowledge graphs into natural language text. Recent advancements in Pretrained Language Models (PLMs) have…