4 citations · 14 across the 32 of their papers we have counts for
4 papers · 2 filters
Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage
Saehyung Lee, Seunghyun Yoon, Trung Bui +2
Multimodal large language models (MLLMs) excel at generating highly detailed captions but often produce hallucinations. Our analysis reveals that existing hallucination detection m…
PEEB: Part-based Image Classifiers with an Explainable and Editable Language Bottleneck
Thang M. Pham, Peijie Chen, Tin Nguyen +3
CLIP-based classifiers rely on the prompt containing a {class name} that is known to the text encoder. Therefore, they perform poorly on new classes or the classes whose names rare…
Scaling Up Video Summarization Pretraining with Large Language Models
Dawit Mureja Argaw, Seunghyun Yoon, Fabian Caba Heilbron +5
Long-form video content constitutes a significant portion of internet traffic, making automated video summarization an essential research problem. However, existing video summariza…
Fine-tuning CLIP Text Encoders with Two-step Paraphrasing
Hyunjae Kim, Seunghyun Yoon, Trung Bui +4
Contrastive language-image pre-training (CLIP) models have demonstrated considerable success across various vision-language tasks, such as text-to-image retrieval, where the model…