3 citations · 3 across the 9 of their papers we have counts for
10 papers
FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models
Youngsun Lim, Cusuh Ham, Pin-Yu Chen +1
Existing text-to-image (T2I) evaluation metrics mainly assess whether generated images align with information explicitly stated in the prompt, but often fail to capture factual req…
The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms
Lingdong Kong, Shaoyuan Xie, Zeying Gong +135
Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under…
Development and Testing for Perception Based Autonomous Landing of a Long-Range QuadPlane
Ashik E Rasul, Humaira Tasnim, Ji Yu Kim +4
QuadPlanes combine the range efficiency of fixed-wing aircraft with the maneuverability of multi-rotor platforms for long-range autonomous missions. In GPS-denied or cluttered urba…
Generative Action Tell-Tales: Assessing Human Motion in Synthesized Videos
Xavier Thomas, Youngsun Lim, Ananya Srinivasan +2
Despite rapid advances in video generative models, robust metrics for evaluating visual and temporal correctness of complex human actions remain elusive. Critically, existing pure-…
Robust Driving QA through Metadata-Grounded Context and Task-Specific Prompts
Seungjun Yu, Junsung Park, Youngsun Lim +1
We present a two-phase vision-language QA system for autonomous driving that answers high-level perception, prediction, and planning questions. In Phase-1, a large multimodal LLM (…
MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection
Hojun Choi, Youngsun Lim, Jaeyo Shin +1
Open-vocabulary object detection (OVD) aims to recognize and localize object categories beyond the training set. Recent approaches leverage vision-language models to generate pseud…
What "Not" to Detect: Negation-Aware VLMs via Structured Reasoning and Token Merging
Inha Kang, Youngsun Lim, Seonho Lee +3
State-of-the-art vision-language models (VLMs) suffer from a critical failure in understanding negation, often referred to as affirmative bias. This limitation is particularly seve…
Label-Augmented Dataset Distillation
Seoungyoon Kang, Youngsun Lim, Hyunjung Shim
Traditional dataset distillation primarily focuses on image representation while often overlooking the important role of labels. In this study, we introduce Label-Augmented Dataset…
Evaluating Image Hallucination in Text-to-Image Generation with Question-Answering
Youngsun Lim, Hojun Choi, Hyunjung Shim
Despite the impressive success of text-to-image (TTI) generation models, existing studies overlook the issue of whether these models accurately convey factual information. In this…
Addressing Image Hallucination in Text-to-Image Generation through Factual Image Retrieval
Youngsun Lim, Hyunjung Shim
Text-to-image generation has shown remarkable progress with the emergence of diffusion models. However, these models often generate factually inconsistent images, failing to accura…