3 citations · 5 across the 17 of their papers we have counts for
8 papers · 1 filter
What MLLMs Learn about When they Learn about Multimodal Reasoning
Jiwan Chung, Neel Joshi, Pratyusha Sharma +2
Evaluation of multimodal reasoning models is typically reduced to a single accuracy score, implicitly treating reasoning as a unitary capability. We introduce MathLens, a benchmark…
Are Any-to-Any Models More Consistent Across Modality Transfers Than Specialists?
Jiwan Chung, Janghan Yoon, Junhyeong Park +4
Any-to-any generative models aim to enable seamless interpretation and generation across multiple modalities within a unified framework, yet their ability to preserve relationships…
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…
Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for Multimodal UI/UX Design Understanding
Jaehyun Jeon, Min Soo Kim, Jang Han Yoon +5
User interface (UI) design goes beyond visuals to shape user experience (UX), underscoring the shift toward UI/UX as a unified concept. While recent studies have explored UI evalua…
Explain with Visual Keypoints Like a Real Mentor! A Benchmark for Multimodal Solution Explanation
Jaewoo Park, Jungyang Park, Dongju Jang +6
With the rapid advancement of mathematical reasoning capabilities in Large Language Models (LLMs), AI systems are increasingly being adopted in educational settings to support stud…
VisEscape: A Benchmark for Evaluating Exploration-driven Decision-making in Virtual Escape Rooms
Seungwon Lim, Sungwoong Kim, Jihwan Yu +3
Escape rooms present a unique cognitive challenge that demands exploration-driven planning: with the sole instruction to 'escape the room', players must actively search their envir…
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…
MASS: Overcoming Language Bias in Image-Text Matching
Jiwan Chung, Seungwon Lim, Sangkyu Lee +1
Pretrained visual-language models have made significant advancements in multimodal tasks, including image-text retrieval. However, a major challenge in image-text matching lies in…