1 citations · 1 across the 5 of their papers we have counts for
5 papers
LED: A Benchmark for Evaluating Layout Error Detection in Document Analysis
Inbum Heo, Taewook Hwang, Jeesu Jung +1
Recent advances in Large Language Models (LLMs) and Large Multimodal Models (LMMs) have improved Document Layout Analysis (DLA), yet structural errors such as region merging, split…
Evaluating Large Language Models on the 2026 Korean CSAT Mathematics Exam: Measuring Mathematical Ability in a Zero-Data-Leakage Setting
Goun Pyeon, Inbum Heo, Jeesu Jung +7
This study systematically evaluated the mathematical reasoning capabilities of Large Language Models (LLMs) using the 2026 Korean College Scholastic Ability Test (CSAT) Mathematics…
LED Benchmark: Diagnosing Structural Layout Errors for Document Layout Analysis
Inbum Heo, Taewook Hwang, Jeesu Jung +1
Recent advancements in Document Layout Analysis through Large Language Models and Multimodal Models have significantly improved layout detection. However, despite these improvement…
FEAT: A Preference Feedback Dataset through a Cost-Effective Auto-Generation and Labeling Framework for English AI Tutoring
Hyein Seo, Taewook Hwang, Yohan Lee +1
In English education tutoring, teacher feedback is essential for guiding students. Recently, AI-based tutoring systems have emerged to assist teachers; however, these systems requi…
Employing Layerwised Unsupervised Learning to Lessen Data and Loss Requirements in Forward-Forward Algorithms
Taewook Hwang, Hyein Seo, Sangkeun Jung
Recent deep learning models such as ChatGPT utilizing the back-propagation algorithm have exhibited remarkable performance. However, the disparity between the biological brain proc…