Learning to Reuse Policies in State Evolvable Environments
Ziqian Zhang, Bohan Yang, Lihe Li, Yuqi Bian, Ruiqi Xue +4 more
2/14/2026
No official code found. Best implementation: zzq-bot/Lapse (5 stars, last commit 2025-05-16).
No official code found. Best implementation: zzq-bot/Lapse (5 stars, last commit 2025-05-16).
A Machine Learning Approach to Duality in Statistical Physics
LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement
Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks
GLoRa: A Benchmark to Evaluate the Ability to Learn Long-Range Dependencies in Graphs
Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way
Adversarial Text to Continuous Image Generation
@article{zhang2026learning,
title = {Learning to Reuse Policies in State Evolvable Environments},
author = {Ziqian Zhang and Bohan Yang and Lihe Li and Yuqi Bian and Ruiqi Xue and Feng Chen and Yichen Li and Lei Yuan and Yang Yu},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:3b10f5518055d75a0f8e3ca5f9bfbbf8136a21ac},
journal = {ICML 2025 2025}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/3b10f5518055d75a0f8e3ca5f9bfbbf8136a21ac)