3 papers
cs.LG2025
Studying the Korean Word-Chain Game with RLVR: Mitigating Reward Conflicts via Curriculum Learning
Donghwan Rho
Reinforcement learning with verifiable rewards (RLVR) is a promising approach for training large language models (LLMs) with stronger reasoning abilities. It has also been applied…
cs.LG2025
Traveling Salesman-Based Token Ordering Improves Stability in Homomorphically Encrypted Language Models
Donghwan Rho, Sieun Seo, Hyewon Sung +2
As users increasingly interact with large language models (LLMs) using private information, secure and encrypted communication becomes essential. Homomorphic encryption (HE) provid…
cs.CR2025
Encryption-Friendly LLM Architecture
Donghwan Rho, Taeseong Kim, Minje Park +4
Large language models (LLMs) offer personalized responses based on user interactions, but this use case raises serious privacy concerns. Homomorphic encryption (HE) is a cryptograp…