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Taehyeong Kim

6 accepted papers

2026

Explain with Visual Keypoints Like a Real Mentor! A Benchmark for Multimodal Solution Explanation

AAAI 2026technical

With the rapid advancement of mathematical reasoning capabilities in Large Language Models (LLMs), AI systems are increasingly being adopted in educational settings to support students’ comprehension of problem-solving processes. However, a critical component remains underexplored in current LLM-gen

Cited by 0SourcePDFScholar
2023

Blending-NeRF: Text-Driven Localized Editing in Neural Radiance Fields

ICCV 2023poster

Text-driven localized editing of 3D objects is particularly difficult as locally mixing the original 3D object with the intended new object and style effects without distorting the object's form is not a straightforward process. To address this issue, we propose a novel NeRF-based model, Blending-Ne…

Cited by 32PDFScholar
2023

Quantitative Manipulation of Custom Attributes on 3D-Aware Image Synthesis

CVPR 2023poster

While 3D-based GAN techniques have been successfully applied to render photo-realistic 3D images with a variety of attributes while preserving view consistency, there has been little research on how to fine-control 3D images without limiting to a specific category of objects of their properties. To…

2021

Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

ICML 2021spotlight

Active learning is widely used to reduce labeling effort and training time by repeatedly querying only the most beneficial samples from unlabeled data. In real-world problems where data cannot be stored indefinitely due to limited storage or privacy issues, the query selection and the model update s…

Cited by 17SourcePDFScholar
2020

Label Propagation Adaptive Resonance Theory for Semi-Supervised Continuous Learning

ICASSP 2020accepted

Semi-supervised learning and continuous learning are fundamental paradigms for human-level intelligence. To deal with real-world problems where labels are rarely given and the opportunity to access the same data is limited, it is necessary to apply these two paradigms in a joined fashion. In this pa…

Cited by 0SourceScholar