2 citations · 4 across the 11 of their papers we have counts for
5 papers · 1 filter
Multi-Robot Motion Planning from Vision and Language using Heat-Inspired Diffusion
Jebeom Chae, Junwoo Chang, Seungho Yeom +2
Diffusion models have recently emerged as powerful tools for robot motion planning by capturing the multi-modal distribution of feasible trajectories. However, their extension to m…
Exploring Multimodal Diffusion Transformers for Enhanced Prompt-based Image Editing
Joonghyuk Shin, Alchan Hwang, Yujin Kim +2
Transformer-based diffusion models have recently superseded traditional U-Net architectures, with multimodal diffusion transformers (MM-DiT) emerging as the dominant approach in st…
Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
Sangmin Bae, Yujin Kim, Reza Bayat +8
Scaling language models unlocks impressive capabilities, but the accompanying computational and memory demands make both training and deployment expensive. Existing efficiency effo…
Guiding Reasoning in Small Language Models with LLM Assistance
Yujin Kim, Euiin Yi, Minu Kim +2
The limited reasoning capabilities of small language models (SLMs) cast doubt on their suitability for tasks demanding deep, multi-step logical deduction. This paper introduces a f…
Self-Training Elicits Concise Reasoning in Large Language Models
Tergel Munkhbat, Namgyu Ho, Seo Hyun Kim +3
Chain-of-thought (CoT) reasoning has enabled large language models (LLMs) to utilize additional computation through intermediate tokens to solve complex tasks. However, we posit th…