collaborators

5 papers

cs.LG2026

AdaBoosting Text Prompts for Vision-Language Models

Seokhee Jin, Changhwan Sung, Sunung Mun +2

The classification accuracy of pretrained Vision-Language Models (VLMs) relies on the quality of the text prompts. Handcrafted templates and Large Language Model (LLM)-generated de…

cs.AI2026

Towards Faithful Agentic XAI: A Verification Method and an Open-World Benchmark for Better Model Faithfulness

Jaechang Kim, Sunung Mun, Seungjoon Lee +2

Explainable AI (XAI) helps users interpret model behavior and identify potential faults. Agentic XAI systems use Large Language Models (LLMs) to make explanations more accessible t…

cs.CV2026

EPIC: Efficient Predicate-Guided Inference-Time Control for Compositional Text-to-Image Generation

Sunung Mun, Sunghyun Cho, Jungseul Ok

Recent text-to-image (T2I) generators can synthesize realistic images, but still struggle with compositional prompts involving multiple objects, counts, attributes, and relations.…

cs.CV2025

World-To-Image: Grounding Text-to-Image Generation with Agent-Driven World Knowledge

Moo Hyun Son, Jintaek Oh, Sun Bin Mun +2

While text-to-image (T2I) models can synthesize high-quality images, their performance degrades significantly when prompted with novel or out-of-distribution (OOD) entities due to…

cs.CV2025

Addressing Text Embedding Leakage in Diffusion-based Image Editing

Sunung Mun, Jinhwan Nam, Sunghyun Cho +1

Text-based image editing, powered by generative diffusion models, lets users modify images through natural-language prompts and has dramatically simplified traditional workflows. D…