1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models
Minji Kim, Hyounghun Kim
Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models should refuse harmful queries (…
cs.CL2024★ 1 cited
Collective Critics for Creative Story Generation
Minwook Bae, Hyounghun Kim
Generating a long story of several thousand words with narrative coherence using Large Language Models (LLMs) has been a challenging task. Previous research has addressed this chal…
cs.CL2024
Revealing the Inherent Instructability of Pre-Trained Language Models
Seokhyun An, Minji Kim, Hyounghun Kim
Instruction tuning -- supervised fine-tuning using instruction-response pairs -- is a key step in making pre-trained large language models (LLMs) instructable. Meanwhile, LLMs perf…