18 citations · 31 across the 27 of their papers we have counts for
29 papers
Mixture of Layers: Dynamic Layer Routing for Visual Reasoning
Jeonghwan Kim, Sofia Stoica, Jiwan Chung +5
Pre-trained vision encoders contain layer-wise visual representations that differ in spatial granularity, semantic abstraction, and sensitivity to local details. However, most Mult…
Where Did It Go Wrong? Process-Level Evaluation of Web Agents with Semantic State Tracking
Jiwan Chung, JiHyuk Byun, Vibhav Vineet +1
Web agents act through long interaction sequences, yet existing benchmarks evaluate only terminal success, discarding all process information and offering little guidance on improv…
Rethinking State Tracking in Recurrent Models Through Error Control Dynamics
Jiwan Chung, Heechan Choi, Seon Joo Kim
The theory of state tracking in recurrent architectures has predominantly focused on expressive capacity: whether a fixed architecture can theoretically realize a set of symbolic t…
Global Geometry Is Not Enough for Vision Representations
Jiwan Chung, Seon Joo Kim
A common assumption in representation learning is that globally well-distributed embeddings support robust and generalizable representations. This focus has shaped both training ob…
A11yn: Aligning LLMs for Web Accessibility-Aware UI Generation
Janghan Yoon, Jaegwan Cho, Junhyeok Kim +4
Large language models can generate visually coherent web UIs from natural language requests, but they frequently violate Web Content Accessibility Guidelines (WCAG), excluding user…
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…
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…
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…
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…
Teaching Metric Distance to Discrete Autoregressive Language Models
Jiwan Chung, Saejin Kim, Yongrae Jo +3
Large language models (LLMs) operate as autoregressive predictors over discrete token vocabularies, a formulation that has enabled their adaptation far beyond natural language to v…
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…
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…
SEAL: Entangled White-box Watermarks on Low-Rank Adaptation
Giyeong Oh, Saejin Kim, Woohyun Cho +4
Recently, LoRA and its variants have become the de facto strategy for training and sharing task-specific versions of large pretrained models, thanks to their efficiency and simplic…
VAGUE: Visual Contexts Clarify Ambiguous Expressions
Heejeong Nam, Jinwoo Ahn, Keummin Ka +2
Human communication often relies on visual cues to resolve ambiguity. While humans can intuitively integrate these cues, AI systems often find it challenging to engage in sophistic…
Towards Visual Text Design Transfer Across Languages
Yejin Choi, Jiwan Chung, Sumin Shim +2
Visual text design plays a critical role in conveying themes, emotions, and atmospheres in multimodal formats such as film posters and album covers. Translating these visual and te…
Can visual language models resolve textual ambiguity with visual cues? Let visual puns tell you!
Jiwan Chung, Seungwon Lim, Jaehyun Jeon +2
Humans possess multimodal literacy, allowing them to actively integrate information from various modalities to form reasoning. Faced with challenges like lexical ambiguity in text,…
CANVAS: Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction
Suhwan Choi, Yongjun Cho, Minchan Kim +9
Real-life robot navigation involves more than just reaching a destination; it requires optimizing movements while addressing scenario-specific goals. An intuitive way for humans to…
Selective Vision is the Challenge for Visual Reasoning: A Benchmark for Visual Argument Understanding
Jiwan Chung, Sungjae Lee, Minseo Kim +4
Visual arguments, often used in advertising or social causes, rely on images to persuade viewers to do or believe something. Understanding these arguments requires selective vision…
Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics
Seungbeen Lee, Seungwon Lim, Seungju Han +9
Recent advancements in Large Language Models (LLMs) have led to their adaptation in various domains as conversational agents. We wonder: can personality tests be applied to these a…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim +8
Algorithmic reasoning refers to the ability to understand the complex patterns behind the problem and decompose them into a sequence of reasoning steps towards the solution. Such n…