3 papers
cs.LG2026
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
Woosung Koh, Jeyoung Jeon, Youngjin Song +4
Current language model training commonly applies multi-task Supervised Fine-Tuning (SFT) using a homogeneous compute budget across all sub-datasets. This approach is fundamentally…
cs.NI2025
Constraint-Compliant Network Optimization through Large Language Models
Youngjin Song, Wookjin Lee, Hong Ki Kim +1
This work develops an LLM-based optimization framework ensuring strict constraint satisfaction in network optimization. While LLMs possess contextual reasoning capabilities, existi…
cs.LG2025
: Scalable Auto-Feedback for LLM-based Chart Generation
Woosung Koh, Jang Han Yoon, MinHyung Lee +7
Generating high-quality charts with Large Language Models (LLMs) presents significant challenges due to limited data and the high cost of scaling through human curation. $\langle \…