2 citations · 2 across the 8 of their papers we have counts for
10 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…
Becoming Experienced Judges: Selective Test-Time Learning for Evaluators
Seungyeon Jwa, Daechul Ahn, Reokyoung Kim +2
Automatic evaluation with large language models, commonly known as LLM-as-a-judge, is now standard across reasoning and alignment tasks. Despite evaluating many samples in deployme…
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…
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…
Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Daechul Ahn, San Kim, Jonghyun Choi
Large Language Models (LLMs) have recently demonstrated impressive action sequence prediction capabilities but often struggle with dynamic, long-horizon tasks such as real-time str…
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO
Daechul Ahn, Yura Choi, San Kim +3
Iterative self-improvement, a concept extending beyond personal growth, has found powerful applications in machine learning, particularly in transforming weak models into strong on…
Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback
Daechul Ahn, Yura Choi, Youngjae Yu +2
Recent advancements in large language models have influenced the development of video large multimodal models (VLMMs). The previous approaches for VLMMs involved Supervised Fine-Tu…
Story Visualization by Online Text Augmentation with Context Memory
Daechul Ahn, Daneul Kim, Gwangmo Song +4
Story visualization (SV) is a challenging text-to-image generation task for the difficulty of not only rendering visual details from the text descriptions but also encoding a long-…
Zero-shot Natural Language Video Localization
Jinwoo Nam, Daechul Ahn, Dongyeop Kang +2
Understanding videos to localize moments with natural language often requires large expensive annotated video regions paired with language queries. To eliminate the annotation cost…