1 citations · 2 across the 12 of their papers we have counts for
8 papers · 1 filter
World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models
Eunsu Kim, Junyeong Park, Na Min An +9
In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large…
Aligned but Stereotypical? How System Prompts Shape Demographic Bias in LLM-Based Text-to-Image Models
NaHyeon Park, Na Min An, Kunhee Kim +3
Text-to-image (T2I) systems increasingly rely on Large Language Model (LLM)-based text conditioning to interpret and expand user prompts. While this improves prompt understanding a…
Are Large Vision-Language Models Ready to Guide Blind and Low-Vision Individuals?
Eunki Kim, Na Min An, Wan Ju Kang +3
Large Vision-Language Models (LVLMs) demonstrate a promising direction for assisting individuals with blindness or low-vision (BLV). Yet, measuring their true utility in real-world…
Blind to Position, Biased in Language: Probing Mid-Layer Representational Bias in Vision-Language Encoders for Zero-Shot Language-Grounded Spatial Understanding
Na Min An, Inha Kang, Minhyun Lee +1
Vision-Language Encoders (VLEs) are widely adopted as the backbone of zero-shot referring image segmentation (RIS), enabling text-guided localization without task-specific training…
When Tom Eats Kimchi: Evaluating Cultural Bias of Multimodal Large Language Models in Cultural Mixture Contexts
Jun Seong Kim, Kyaw Ye Thu, Javad Ismayilzada +6
In a highly globalized world, it is important for multi-modal large language models (MLLMs) to recognize and respond correctly to mixed-cultural inputs. For example, a model should…
Sightation Counts: Leveraging Sighted User Feedback in Building a BLV-aligned Dataset of Diagram Descriptions
Wan Ju Kang, Eunki Kim, Na Min An +4
Often, the needs and visual abilities differ between the annotator group and the end user group. Generating detailed diagram descriptions for blind and low-vision (BLV) users is on…
How Blind and Low-Vision Individuals Prefer Large Vision-Language Model-Generated Scene Descriptions
Na Min An, Eunki Kim, Wan Ju Kang +3
For individuals with blindness or low vision (BLV), navigating complex environments can pose serious risks. Large Vision-Language Models (LVLMs) show promise for generating scene d…
Diffusion Models Through a Global Lens: Are They Culturally Inclusive?
Zahra Bayramli, Ayhan Suleymanzade, Na Min An +5
Text-to-image diffusion models have recently enabled the creation of visually compelling, detailed images from textual prompts. However, their ability to accurately represent vario…