5 papers
RTSGameBench: An RTS Benchmark for Strategic Reasoning by Vision-Language Models
San Kim, Daechul Ahn, Reokyoung Kim +3
Modern Vision-Language Models (VLMs) often struggle with strategic reasoning, i.e., anticipating and influencing other agents' actions, under uncertainty in competitive and coopera…
SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models
Hyeonbeom Choi, Daechul Ahn, Youhan Lee +3
Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gaining attention to enhance robustness b…
BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands
Seongwon Cho, Daechul Ahn, Donghyun Shin +3
Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their world representation under dynamic environ…
GenOL: Generating Diverse Examples for Name-only Online Learning
Minhyuk Seo, Seongwon Cho, Minjae Lee +4
Online learning methods often rely on supervised data. However, under data distribution shifts, such as in continual learning (CL), where continuously arriving online data streams…
What Happens When: Learning Temporal Orders of Events in Videos
Daechul Ahn, Yura Choi, Hyeonbeom Choi +3
Video Large Multimodal Models (VLMMs) have shown impressive performance in video understanding, yet their ability to accurately capture the temporal order of multiple events remain…