5 papers
v1: Learning to Point Visual Tokens for Multimodal Grounded Reasoning
Jiwan Chung, Junhyeok Kim, Siyeol Kim +3
When thinking with images, humans rarely rely on a single glance: they revisit visual evidence while reasoning. In contrast, most Multimodal Language Models encode an image once to…
GuideDog: A Real-World Egocentric Multimodal Dataset for Blind and Low-Vision Accessibility-Aware Guidance
Junhyeok Kim, Jaewoo Park, Junhee Park +5
For people affected by blindness and low vision (BLV), safe and independent navigation remains a major challenge, impacting over 2.2 billion individuals worldwide. Although multimo…
A11YN: aligning LLMs for accessible web UI code generation
Janghan Yoon, Jaegwan Cho, Junhyeok Kim +3
Large language models (LLMs) have recently demonstrated strong capabilities in generating functional and aesthetic web interfaces directly from instructions. However, these models…
Speaking Beyond Language: A Large-Scale Multimodal Dataset for Learning Nonverbal Cues from Video-Grounded Dialogues
Youngmin Kim, Jiwan Chung, Jisoo Kim +5
Nonverbal communication is integral to human interaction, with gestures, facial expressions, and body language conveying critical aspects of intent and emotion. However, existing l…
EgoSpeak: Learning When to Speak for Egocentric Conversational Agents in the Wild
Junhyeok Kim, Min Soo Kim, Jiwan Chung +5
Predicting when to initiate speech in real-world environments remains a fundamental challenge for conversational agents. We introduce EgoSpeak, a novel framework for real-time spee…