Knowledge Graph Injection for Reinforcement Learning. - Robert Wardenga; Liubov Kovriguina; Dmitrii Pliukhin; Daniil Radyush; Ivan SmoliakoV; Yuan Xue 005; Henrik Müller; Aleksei Pismerov; Dmitry Mouromtsev; Daniel Kudenko (DL4KG@ISWC, 2023)

Graph learning-based generation of abstractions for reinforcement learning. - Yuan Xue 005; Daniel Kudenko; Megha Khosla (Neural Comput. Appl., 2025)

CubeletWorld: A New Abstraction for Scalable 3D Modeling. - Azlaan Mustafa Samad; Hoang H. Nguyen; Lukas Berg; Henrik Müller; Yuan Xue 005; Daniel Kudenko; Zahra Ahmadi (CoRR, 2025)

Causality-Based Data-Augmentation for Offline Reinforcement Learning. - Wei Zhang 309; Azlaan Mustafa Samad; Yuan Xue 005; Daniel Kudenko (IEEE Access, 2026)

Towards unbiased action value estimation in reinforcement learning. - Yuan Xue 005; Daniel Kudenko; Megha Khosla (Neurocomputing, 2026)

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization. - Yuan Xue 005; Daniel Kudenko; Megha Khosla (CoRR, 2026)