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20232026
most citedPCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

1 citations · 2 across the 11 of their papers we have counts for

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cs.AI2026

When Saying No Makes Better Videos: Designing Dual Gatekeeping for Pedagogically Grounded AI Content Creation

Yearim Kim, Injun Baek, Nojun Kwak

To prevent the adoption of aesthetically polished but pedagogically flawed AI content, we study a video authoring pipeline featuring two layers of structured refusal. The first lay…

cs.AI2026

Multiverse: Language-Conditioned Multi-Game Level Blending via Shared Representation

In-Chang Baek, Jiyun Jung, Geum-Hwan Hwang +2

Text-to-level generation aims to translate natural language descriptions into structured game levels, enabling intuitive control over procedural content generation. While prior tex…

cs.AI2025

Human-Aligned Procedural Level Generation Reinforcement Learning via Text-Level-Sketch Shared Representation

In-Chang Baek, Seoyoung Lee, Sung-Hyun Kim +2

Human-aligned AI is a critical component of co-creativity, as it enables models to accurately interpret human intent and generate controllable outputs that align with design goals…

cs.AI2025

IPCGRL: Language-Instructed Reinforcement Learning for Procedural Level Generation

In-Chang Baek, Sung-Hyun Kim, Seo-Young Lee +2

Recent research has highlighted the significance of natural language in enhancing the controllability of generative models. While various efforts have been made to leverage natural…

cs.AI2025★ 1 cited

PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

In-Chang Baek, Sung-Hyun Kim, Sam Earle +4

Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, several studies have explored rew…

cs.AI2024

ChatPCG: Large Language Model-Driven Reward Design for Procedural Content Generation

In-Chang Baek, Tae-Hwa Park, Jin-Ha Noh +2

Driven by the rapid growth of machine learning, recent advances in game artificial intelligence (AI) have significantly impacted productivity across various gaming genres. Reward d…

cs.AI2023★ 1 cited

RaidEnv: Exploring New Challenges in Automated Content Balancing for Boss Raid Games

Hyeon-Chang Jeon, In-Chang Baek, Cheong-mok Bae +7

The balance of game content significantly impacts the gaming experience. Unbalanced game content diminishes engagement or increases frustration because of repetitive failure. Altho…