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Dongmin Choi

4 accepted papers

2025

ELDET: Early-Learning Distillation with Noisy Labels for Object Detection

NeurIPS 2025poster

The performance of learning-based object detection algorithms, which attempt to both classify and locate objects within images, is determined largely by the quality of the annotated dataset used for training. Two types of labelling noises are prevalent: objects that are incorrectly classified (categ…

Cited by 0SourceScholar
2025

PVP: An Image Dataset for Personalized Visual Persuasion with Persuasion Strategies, Viewer Characteristics, and Persuasiveness Ratings

ACL 2025long

Visual persuasion, which uses visual elements to influence cognition and behaviors, is crucial in fields such as advertising and politicalcommunication. With recent advancements in artificial intelligence, there is growing potential to develop persuasive systems that automatically generate persuasiv…

2025

Value Portrait: Assessing Language Models’ Values through Psychometrically and Ecologically Valid Items

ACL 2025long

The importance of benchmarks for assessing the values of language models has been pronounced due to the growing need of more authentic, human-aligned responses. However, existing benchmarks rely on human or machine annotations that are vulnerable to value-related biases. Furthermore, the tested scen…

Cited by 0SourcePDFScholar
2024

iDet3D: Towards Efficient Interactive Object Detection for LiDAR Point Clouds

AAAI 2024technical

Accurately annotating multiple 3D objects in LiDAR scenes is laborious and challenging. While a few previous studies have attempted to leverage semi-automatic methods for cost-effective bounding box annotation, such methods have limitations in efficiently handling numerous multi-class objects. To ef…

Cited by 5SourcePDFScholar