Hierarchical Entity-Centric Reinforcement Learning (HECRL)

ICLR 2026

Code • Project Website • arXiv • OpenReview

Details

Official release of the datasets from the paper "Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion" by Dan Haramati, Carl Qi, Tal Daniel, Amy Zhang, Aviv Tamar and George Konidaris.

Datasets contain 128x128 RGB images, state information, actions, and information for calculating goal-conditioned rewards.

For RL training on image-based tasks, images in the dataset are preprocessed into latent representations using visual encoders which were pretrained on the same dataset.

Citation

Please consider citing our work if you find our paper or this repository useful.

@inproceedings{
haramati2026hierarchical,
title={Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion},
author={Dan Haramati and Carl Qi and Tal Daniel and Amy Zhang and Aviv Tamar and George Konidaris},
booktitle={The Fourteenth International Conference on Learning Representations},
year={2026},
url={https://openreview.net/forum?id=TimC6hxVHj}
}