5 papers
Restoration-Aligned Generative Flow Models for Blind Motion Deblurring
Insoo Kim, Jinwoo Shin
Generative flow models offer powerful priors learned from large-scale natural images, but directly adapting them to restoration tasks such as motion deblurring causes severe fideli…
Correct Answers from Sound Reasoning: Verifiable Process Supervision for Language Models
Kyuyoung Kim, Kevin Wang, Yunfei Xie +7
Training language models to produce both correct answers and sound reasoning remains an open challenge. Reinforcement learning with verifiable rewards typically optimizes only fina…
Parallel Key-Value Cache Fusion for Position Invariant RAG
Philhoon Oh, Jinwoo Shin, James Thorne
Recent advancements in Large Language Models (LLMs) underscore the necessity of Retrieval Augmented Generation (RAG) to leverage external information. However, LLMs are sensitive t…
Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models
Sanghyun Kim, Moonseok Choi, Jinwoo Shin +1
Fine-tuning text-to-image diffusion models is widely used for personalization and adaptation for new domains. In this paper, we identify a critical vulnerability of fine-tuning: sa…
Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion
Sanghyun Kim, Seohyeon Jung, Balhae Kim +3
This paper addresses the societal concerns arising from large-scale text-to-image diffusion models for generating potentially harmful or copyrighted content. Existing models rely h…