9 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.AI2025
Aligning Large Language Models with Procedural Rules: An Autoregressive State-Tracking Prompting for In-Game Trading
Minkyung Kim, Junsik Kim, Woongcheol Yang +2
Large Language Models (LLMs) enable dynamic game interactions but fail to follow essential procedural flows in rule-governed trading systems, eroding player trust. This work resolv…
cs.AI2025
State-Inference-Based Prompting for Natural Language Trading with Game NPCs
Minkyung Kim, Junsik Kim, Hwidong Bae +3
Large Language Models enable dynamic game interactions but struggle with rule-governed trading systems. Current implementations suffer from rule violations, such as item hallucinat…
cs.NI2020★ 9 cited
A Reinforcement Learning Formulation of the Lyapunov Optimization: Application to Edge Computing Systems with Queue Stability
Sohee Bae, Seungyul Han, Youngchul Sung
In this paper, a deep reinforcement learning (DRL)-based approach to the Lyapunov optimization is considered to minimize the time-average penalty while maintaining queue stability.…