4 papers
RAIN: Robotic Task Generalization with Region-Aware Interaction Networks
Seunghun Lee, Kyuhwan Shim, Yeogyeong Song +5
Existing vision-language-action (VLA) models benefit from large-scale vision-language pretraining, but tend to memorize training trajectories, limiting their ability to adapt learn…
Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation
Jisoo Kim, Jungbin Cho, Sanghyeok Chu +9
Humans learn not only how their bodies move, but also how the surrounding world responds to their actions. In contrast, while recent Vision-Language-Action (VLA) models exhibit imp…
MASH-VLM: Mitigating Action-Scene Hallucination in Video-LLMs through Disentangled Spatial-Temporal Representations
Kyungho Bae, Jinhyung Kim, Sihaeng Lee +3
In this work, we tackle action-scene hallucination in Video Large Language Models (Video-LLMs), where models incorrectly predict actions based on the scene context or scenes based…
OmniSplat: Taming Feed-Forward 3D Gaussian Splatting for Omnidirectional Images with Editable Capabilities
Suyoung Lee, Jaeyoung Chung, Kihoon Kim +4
Feed-forward 3D Gaussian splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Alth…