11 papers
AgentPSO: Evolving Agent Reasoning Skill via Multi-agent Particle Swarm Optimization
Hyunmin Hwang, Jaemin Kim, Choonghan Kim +2
Multi-agent reasoning has shown promise for improving the problem-solving ability of large language models by allowing multiple agents to explore diverse reasoning paths. However,…
Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models
Jaemin Kim, Jong Chul Ye
Retrieval-Augmented Generation (RAG) improves factual grounding by incorporating external knowledge into language model generation. However, when retrieved context is noisy, unreli…
CLaD: Planning with Grounded Foresight via Cross-Modal Latent Dynamics
Andrew Jeong, Jaemin Kim, Sebin Lee +1
Robotic manipulation involves kinematic and semantic transitions that are inherently coupled via underlying actions. However, existing approaches plan within either semantic or lat…
DMD-augmented Unpaired Neural Schrödinger Bridge for Ultra-Low Field MRI Enhancement
Youngmin Kim, Jaeyun Shin, Jeongchan Kim +5
Ultra Low Field (64 mT) brain MRI improves accessibility but suffers from reduced image quality compared to 3 T. As paired 64 mT - 3 T scans are scarce, we propose an unpaired 64 m…
Dementia-R1: Reinforced Pretraining and Reasoning from Unstructured Clinical Notes for Real-World Dementia Prognosis
Choonghan Kim, Hyunmin Hwang, Hangeol Chang +4
While Large Language Models (LLMs) have shown strong performance on clinical text understanding, they struggle with longitudinal prediction tasks such as dementia prognosis, which…
Training-Free Reward-Guided Image Editing via Trajectory Optimal Control
Jinho Chang, Jaemin Kim, Jong Chul Ye
Recent advancements in diffusion and flow-matching models have demonstrated remarkable capabilities in high-fidelity image synthesis. A prominent line of research involves reward-g…
Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs
Jaemin Kim, Hangeol Chang, Hyunmin Hwang +2
Large Language Models (LLMs) have demonstrated remarkable general capabilities, but enhancing skills such as reasoning often demands substantial computational resources and may com…
FreeGuide: Training-Free Text-to-Video Alignment using Image LVLM
Jaemin Kim, Bryan Sangwoo Kim, Jong Chul Ye
Diffusion models have achieved impressive results in generative tasks for text-to-video (T2V) synthesis. However, achieving accurate text alignment in T2V generation remains challe…
Optical-Flow Guided Prompt Optimization for Coherent Video Generation
Hyelin Nam, Jaemin Kim, Dohun Lee +1
While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency. Within diffusion frameworks, guidance…
Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
Won Jun Kim, Hyungjin Chung, Jaemin Kim +3
Gradient-based methods are a prototypical family of explainability techniques, especially for image-based models. Nonetheless, they have several shortcomings in that they (1) requi…
Generalized Consistency Trajectory Models for Image Manipulation
Beomsu Kim, Jaemin Kim, Jeongsol Kim +1
Diffusion models (DMs) excel in unconditional generation, as well as on applications such as image editing and restoration. The success of DMs lies in the iterative nature of diffu…