CQM: Curriculum Reinforcement Learning with a Quantized World Model

26 October 2023

Papers citing "CQM: Curriculum Reinforcement Learning with a Quantized World Model"

6 / 6 papers shown

Title
Imagine, Verify, Execute: Memory-Guided Agentic Exploration with Vision-Language Models Seungjae Lee Daniel Ekpo Haowen Liu Furong Huang Abhinav Shrivastava Jia-Bin Huang LM&Ro 40 0 0 12 May 2025
Adversarial Environment Design via Regret-Guided Diffusion Models Hojun Chung Junseo Lee Minsoo Kim Dohyeong Kim Songhwai Oh 31 0 0 25 Oct 2024
CurricuLLM: Automatic Task Curricula Design for Learning Complex Robot Skills using Large Language Models Kanghyun Ryu Qiayuan Liao Zhongyu Li K. Sreenath Negar Mehr Negar Mehr LM&Ro 180 3 0 27 Sep 2024
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning Hyungho Na IL-Chul Moon 43 1 0 30 May 2024
Planning Goals for Exploration E. Hu Richard Chang Oleh Rybkin Dinesh Jayaraman 43 24 0 23 Mar 2023
DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning Seungjae Lee Jigang Kim Inkyu Jang H. J. Kim OffRL 27 10 0 11 Oct 2022