Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Yupei, Huang, Biwei, Feng, Fan, Wang, Xinyue, Tu, Shikui, Xu, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge
by: Yang, Yupei, et al.
Published: (2024)
by: Yang, Yupei, et al.
Published: (2024)
Factored Causal Representation Learning for Robust Reward Modeling in RLHF
by: Yang, Yupei, et al.
Published: (2026)
by: Yang, Yupei, et al.
Published: (2026)
Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
by: Lin, Guang, et al.
Published: (2026)
by: Lin, Guang, et al.
Published: (2026)
Transformer Is Inherently a Causal Learner
by: Wang, Xinyue, et al.
Published: (2026)
by: Wang, Xinyue, et al.
Published: (2026)
Full-Atom Peptide Design via Riemannian-Euclidean Bayesian Flow Networks
by: Qian, Hao, et al.
Published: (2025)
by: Qian, Hao, et al.
Published: (2025)
Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number
by: Zhou, Jingyuan, et al.
Published: (2025)
by: Zhou, Jingyuan, et al.
Published: (2025)
Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems
by: Liang, Hao, et al.
Published: (2025)
by: Liang, Hao, et al.
Published: (2025)
Reinforcement Learning for Causal Discovery without Acyclicity Constraints
by: Duong, Bao, et al.
Published: (2024)
by: Duong, Bao, et al.
Published: (2024)
Causal Representation Meets Stochastic Modeling under Generic Geometry
by: Ren, Jiaxu, et al.
Published: (2026)
by: Ren, Jiaxu, et al.
Published: (2026)
Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks
by: Jin, Songyao, et al.
Published: (2025)
by: Jin, Songyao, et al.
Published: (2025)
THFlow: A Temporally Hierarchical Flow Matching Framework for 3D Peptide Design
by: Huang, Dengdeng, et al.
Published: (2025)
by: Huang, Dengdeng, et al.
Published: (2025)
Hallucination-Resistant Relation Extraction via Dependency-Aware Sentence Simplification and Two-tiered Hierarchical Refinement
by: Yang, Yupei, et al.
Published: (2025)
by: Yang, Yupei, et al.
Published: (2025)
MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment
by: Wang, Ziyan, et al.
Published: (2023)
by: Wang, Ziyan, et al.
Published: (2023)
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
by: Lin, Haohong, et al.
Published: (2024)
by: Lin, Haohong, et al.
Published: (2024)
Policy-Guided Causal State Representation for Offline Reinforcement Learning Recommendation
by: Wang, Siyu, et al.
Published: (2025)
by: Wang, Siyu, et al.
Published: (2025)
Rethinking State Disentanglement in Causal Reinforcement Learning
by: Cao, Haiyao, et al.
Published: (2024)
by: Cao, Haiyao, et al.
Published: (2024)
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
by: Zhang, Wanpeng, et al.
Published: (2023)
by: Zhang, Wanpeng, et al.
Published: (2023)
Differentiable Causal Discovery For Latent Hierarchical Causal Models
by: Prashant, Parjanya, et al.
Published: (2024)
by: Prashant, Parjanya, et al.
Published: (2024)
Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
by: Wang, Xinyue, et al.
Published: (2025)
by: Wang, Xinyue, et al.
Published: (2025)
A Fast Kernel-based Conditional Independence test with Application to Causal Discovery
by: Schacht, Oliver, et al.
Published: (2025)
by: Schacht, Oliver, et al.
Published: (2025)
Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
by: Li, Siyang, et al.
Published: (2025)
by: Li, Siyang, et al.
Published: (2025)
Causal Information Prioritization for Efficient Reinforcement Learning
by: Cao, Hongye, et al.
Published: (2025)
by: Cao, Hongye, et al.
Published: (2025)
CausalGDP: Causality-Guided Diffusion Policies for Reinforcement Learning
by: Xiao, Xiaofeng, et al.
Published: (2026)
by: Xiao, Xiaofeng, et al.
Published: (2026)
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
by: Komanduri, Aneesh, et al.
Published: (2023)
by: Komanduri, Aneesh, et al.
Published: (2023)
VLGOR: Visual-Language Knowledge Guided Offline Reinforcement Learning for Generalizable Agents
by: Liu, Pengsen, et al.
Published: (2026)
by: Liu, Pengsen, et al.
Published: (2026)
Concept Factorization via Self-Representation and Adaptive Graph Structure Learning
by: Yang, Zhengqin, et al.
Published: (2025)
by: Yang, Zhengqin, et al.
Published: (2025)
CGRL: Causal-Guided Representation Learning for Graph Out-of-Distribution Generalization
by: Lu, Bowen, et al.
Published: (2026)
by: Lu, Bowen, et al.
Published: (2026)
Towards Unsupervised Causal Representation Learning via Latent Additive Noise Model Causal Autoencoders
by: Ong, Hans Jarett J., et al.
Published: (2025)
by: Ong, Hans Jarett J., et al.
Published: (2025)
Towards Identifiability of Hierarchical Temporal Causal Representation Learning
by: Li, Zijian, et al.
Published: (2025)
by: Li, Zijian, et al.
Published: (2025)
Optimal Kernel Choice for Score Function-based Causal Discovery
by: Wang, Wenjie, et al.
Published: (2024)
by: Wang, Wenjie, et al.
Published: (2024)
Robust and Adaptive Spectral Method for Representation Multi-Task Learning with Contamination
by: Huang, Yian, et al.
Published: (2025)
by: Huang, Yian, et al.
Published: (2025)
SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch
by: Feng, Shengyu, et al.
Published: (2024)
by: Feng, Shengyu, et al.
Published: (2024)
CausalCOMRL: Context-Based Offline Meta-Reinforcement Learning with Causal Representation
by: Zhang, Zhengzhe, et al.
Published: (2025)
by: Zhang, Zhengzhe, et al.
Published: (2025)
DreamSAC: Learning Hamiltonian World Models via Symmetry Exploration
by: Tang, Jinzhou, et al.
Published: (2026)
by: Tang, Jinzhou, et al.
Published: (2026)
Towards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach
by: Yang, Sungwook, et al.
Published: (2024)
by: Yang, Sungwook, et al.
Published: (2024)
Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement Learning
by: Zhou, Shicheng, et al.
Published: (2024)
by: Zhou, Shicheng, et al.
Published: (2024)
Towards the Causal Complete Cause of Multi-Modal Representation Learning
by: Wang, Jingyao, et al.
Published: (2024)
by: Wang, Jingyao, et al.
Published: (2024)
On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
by: Wang, Bokun, et al.
Published: (2024)
by: Wang, Bokun, et al.
Published: (2024)
Generative design and validation of therapeutic peptides for glioblastoma based on a potential target ATP5A
by: Qian, Hao, et al.
Published: (2025)
by: Qian, Hao, et al.
Published: (2025)
ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation
by: Feng, Haoan, et al.
Published: (2026)
by: Feng, Haoan, et al.
Published: (2026)
Similar Items
-
Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge
by: Yang, Yupei, et al.
Published: (2024) -
Factored Causal Representation Learning for Robust Reward Modeling in RLHF
by: Yang, Yupei, et al.
Published: (2026) -
Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
by: Lin, Guang, et al.
Published: (2026) -
Transformer Is Inherently a Causal Learner
by: Wang, Xinyue, et al.
Published: (2026) -
Full-Atom Peptide Design via Riemannian-Euclidean Bayesian Flow Networks
by: Qian, Hao, et al.
Published: (2025)