Discrete Latent Plans via Semantic Skill Abstractions
Haobin Jiang, Jiangxing Wang, Zongqing Lu
2/12/2026
No official code found. Best implementation: PKU-RL/LADS (6 stars, last commit 2025-05-05).
No official code found. Best implementation: PKU-RL/LADS (6 stars, last commit 2025-05-05).
Causal Imitation Learning via Inverse Reinforcement Learning
Learning Graph Representation via Graph Entropy Maximization
Offline Transition Modeling via Contrastive Energy Learning
Improving Depth Completion via Depth Feature Upsampling
Boosting Causal Discovery via Adaptive Sample Reweighting
Improving Adversarial Robustness via Information Bottleneck Distillation
@article{jiang2026discrete,
title = {Discrete Latent Plans via Semantic Skill Abstractions},
author = {Haobin Jiang and Jiangxing Wang and Zongqing Lu},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:1aef5dc9e20e89ee8fb3067e9217e59a9494b917},
journal = {ICLR 2025 2025}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/1aef5dc9e20e89ee8fb3067e9217e59a9494b917)