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20222026
most citedUnsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning

5 citations · 12 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

Self-Distilling Future Video Representations for World Action Models

Huiwon Jang, Suhyeok Jang, Hyeonmo Kang +3

World Action Models (WAMs) have emerged as a promising approach to learning generalist robot policies using rich spatiotemporal priors from pre-trained video diffusion models. A re…

cs.RO2026

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…

cs.RO2026

Modular Sensory Stream for Integrating Physical Feedback in Vision-Language-Action Models

Jimin Lee, Huiwon Jang, Myungkyu Koo +2

Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approaches attempt to incorporate phy…

cs.RO2025

ContextVLA: Vision-Language-Action Model with Amortized Multi-Frame Context

Huiwon Jang, Sihyun Yu, Heeseung Kwon +3

Leveraging temporal context is crucial for success in partially observable robotic tasks. However, prior work in behavior cloning has demonstrated inconsistent performance gains wh…

cs.RO2025

Robot-R1: Reinforcement Learning for Enhanced Embodied Reasoning in Robotics

Dongyoung Kim, Sumin Park, Huiwon Jang +3

Large Vision-Language Models (LVLMs) have recently shown great promise in advancing robotics by combining embodied reasoning with robot control. A common approach involves training…