6 papers
DEO: Training-Free Direct Embedding Optimization for Negation-Aware Retrieval
Taegyeong Lee, Jiwon Park, Seunghyun Hwang +1
Recent advances in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) have enabled diverse retrieval methods. However, existing retrieval methods often fail to a…
QGuard:Question-based Zero-shot Guard for Multi-modal LLM Safety
Taegyeong Lee, Jeonghwa Yoo, Hyoungseo Cho +2
The recent advancements in Large Language Models(LLMs) have had a significant impact on a wide range of fields, from general domains to specialized areas. However, these advancemen…
Exploring Diffusion Models for Generative Forecasting of Financial Charts
Taegyeong Lee, Jiwon Park, Kyunga Bang +2
Recent advances in generative models have enabled significant progress in tasks such as generating and editing images from text, as well as creating videos from text prompts, and t…
Multi-aspect Knowledge Distillation with Large Language Model
Taegyeong Lee, Jinsik Bang, Soyeong Kwon +1
Recent advancements in deep learning have significantly improved performance on computer vision tasks. Previous image classification methods primarily modify model architectures or…
Grid Diffusion Models for Text-to-Video Generation
Taegyeong Lee, Soyeong Kwon, Taehwan Kim
Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images…
Zero-shot Text-guided Infinite Image Synthesis with LLM guidance
Soyeong Kwon, Taegyeong Lee, Taehwan Kim
Text-guided image editing and generation methods have diverse real-world applications. However, text-guided infinite image synthesis faces several challenges. First, there is a lac…