12 papers
Verifier-free Test-Time Sampling for Vision-Language-Action Models
Suhyeok Jang, Dongyoung Kim, Changyeon Kim +2
Vision-Language-Action models (VLAs) have demonstrated remarkable performance in robot control. However, they remain fundamentally limited in tasks that require high precision due…
Contrastive Representation Regularization for Vision-Language-Action Models
Taeyoung Kim, Jimin Lee, Myungkyu Koo +5
Vision-Language-Action (VLA) models have shown strong capabilities in robot manipulation by leveraging rich representations from pre-trained Vision-Language Models (VLMs). However,…
Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model
John Won, Kyungmin Lee, Huiwon Jang +2
Augmenting vision-language-action models (VLAs) with world models is promising for robotic policy learning but faces challenges in jointly predicting states and actions due to the…
Efficient LLM Collaboration via Planning
Byeongchan Lee, Jonghoon Lee, Dongyoung Kim +4
Recently, large language models (LLMs) have demonstrated strong performance, ranging from simple to complex tasks. However, while large models achieve remarkable results across div…
RLDX-1 Technical Report
Dongyoung Kim, Huiwon Jang, Myungkyu Koo +65
While Vision-Language-Action models (VLAs) have shown remarkable progress toward human-like generalist robotic policies through the versatile intelligence (i.e. broad scene underst…
SpatialBoost: Enhancing Visual Representation through Language-Guided Reasoning
Byungwoo Jeon, Dongyoung Kim, Huiwon Jang +2
Despite the remarkable success of large-scale pre-trained image representation models (i.e., vision encoders) across various vision tasks, they are predominantly trained on 2D imag…