9 citations · 9 across the 5 of their papers we have counts for
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cs.LG2026
Variance-Averse -Step Offline Reinforcement Learning for Sparse Long-Horizon Environments
Guhyeon Kang, Minhae Kwon
Generative actors are transforming offline reinforcement learning (RL) by enabling expressive policy classes that model complex action distributions. However, this expressiveness a…
cs.LG2026
Simple Actors and Deep Critics for Scalable Reinforcement Learning
Guhyeon Kang, Jaehwi Lee, Minhae Kwon
Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, which capture multimodal behavi…
cs.LG2026
Multi: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments
Sangeun Park, Minhae Kwon
A central goal of large language model (LLM) research is to build agentic systems that can plan, act, and adapt through sustained interaction with dynamic environments. While recen…