4 papers · 1 filter
Alignment Data Map for Efficient Preference Data Selection and Diagnosis
Seohyeong Lee, Eunwon Kim, Hwaran Lee +1
Human preference data is essential for aligning large language models (LLMs) with human values, but collecting such data is often costly and inefficient-motivating the need for eff…
Guaranteed Generation from Large Language Models
Minbeom Kim, Thibaut Thonet, Jos Rozen +3
As large language models (LLMs) are increasingly used across various applications, there is a growing need to control text generation to satisfy specific constraints or requirement…
Drift: Decoding-time Personalized Alignments with Implicit User Preferences
Minbeom Kim, Kang-il Lee, Seongho Joo +3
Personalized alignments for individual users have been a long-standing goal in large language models (LLMs). We introduce Drift, a novel framework that personalizes LLMs at decodin…
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge
Jiyoung Lee, Minwoo Kim, Seungho Kim +4
For Large Language Models (LLMs) to be effectively deployed in a specific country, they must possess an understanding of the nation's culture and basic knowledge. To this end, we i…