Cover Image

Learning Local Causal World Models with State Space Models and Attention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Petri, Francesco, Asprino, Luigi, Gangemi, Aldo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Transformers and Slot Encoding for Sample Efficient Physical World Modelling
by: Petri, Francesco, et al.
Published: (2024)

Do Language Models Understand Morality? Towards a Robust Detection of Moral Content
by: Bulla, Luana, et al.
Published: (2024)

Explainable Moral Values: a neuro-symbolic approach to value classification
by: Lazzari, Nicolas, et al.
Published: (2024)

A Supervised Machine-Learning Approach For Turboshaft Engine Dynamic Modeling Under Real Flight Conditions
by: Paniccia, Damiano, et al.
Published: (2025)

CausalMamba: Interpretable State Space Modeling for Temporal Rumor Causality
by: Zhan, Xiaotong, et al.
Published: (2025)

Explainable Reinforcement Learning via a Causal World Model
by: Yu, Zhongwei, et al.
Published: (2023)

Disentangling Dynamical Systems: Causal Representation Learning Meets Local Sparse Attention
by: Baumgartner, Markus W., et al.
Published: (2026)

Causal Learning with the Invariance Principle
by: Montagna, Francesco, et al.
Published: (2026)

Generalization Error Analysis for Selective State-Space Models Through the Lens of Attention
by: Honarpisheh, Arya, et al.
Published: (2025)

Curious Causality-Seeking Agents Learn Meta Causal World
by: Zhao, Zhiyu, et al.
Published: (2025)

Federated Granger Causality Learning for Interdependent Clients with State Space Representation
by: Mohanty, Ayush, et al.
Published: (2025)

FACTS: A Factored State-Space Framework For World Modelling
by: Nanbo, Li, et al.
Published: (2024)

Object-Centric World Models for Causality-Aware Reinforcement Learning
by: Nishimoto, Yosuke, et al.
Published: (2025)

WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
by: Solozabal, Ruben, et al.
Published: (2026)

Invariant Causal Prediction with Local Models
by: Mey, Alexander, et al.
Published: (2024)

Extracting the Multiscale Causal Backbone of Brain Dynamics
by: D'Acunto, Gabriele, et al.
Published: (2023)

Exemplar-Free Continual Learning for State Space Models
by: Lee, Isaac Ning, et al.
Published: (2025)

Learning to Dissipate Energy in Oscillatory State-Space Models
by: Boyer, Jared, et al.
Published: (2025)

Latent Matters: Learning Deep State-Space Models
by: Klushyn, Alexej, et al.
Published: (2026)

Causal-Symbolic Meta-Learning (CSML): Inducing Causal World Models for Few-Shot Generalization
by: S, Mohamed Zayaan
Published: (2025)

Attention Deficits in Language Models: Causal Explanations for Procedural Hallucinations
by: Karim, Ahmed, et al.
Published: (2026)

An Asymmetric Independence Model for Causal Discovery on Path Spaces
by: Manten, Georg, et al.
Published: (2025)

Learning Abstract World Models with a Group-Structured Latent Space
by: Delliaux, Thomas, et al.
Published: (2025)

Cellular Traffic Prediction via Deep State Space Models with Attention Mechanism
by: Ma, Hui, et al.
Published: (2025)

Spectral State Space Models
by: Agarwal, Naman, et al.
Published: (2023)

Neurosymbolic Graph Enrichment for Grounded World Models
by: De Giorgis, Stefano, et al.
Published: (2024)

Graph Mamba: Towards Learning on Graphs with State Space Models
by: Behrouz, Ali, et al.
Published: (2024)

CausalARC: Abstract Reasoning with Causal World Models
by: Maasch, Jacqueline, et al.
Published: (2025)

Towards Causal Foundation Model: on Duality between Causal Inference and Attention
by: Zhang, Jiaqi, et al.
Published: (2023)

Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
by: Sieber, Jerome, et al.
Published: (2024)

Taipan: Efficient and Expressive State Space Language Models with Selective Attention
by: Van Nguyen, Chien, et al.
Published: (2024)

Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery
by: Darvariu, Victor-Alexandru, et al.
Published: (2023)

Context-Selective State Space Models: Feedback is All You Need
by: Zattra, Riccardo, et al.
Published: (2025)

Locality Sensitive Sparse Encoding for Learning World Models Online
by: Liu, Zichen, et al.
Published: (2024)

Regularization-Based Efficient Continual Learning in Deep State-Space Models
by: Zhang, Yuanhang, et al.
Published: (2024)

Towards a theory of Façade-X data access: satisfiability of SPARQL basic graph patterns
by: Asprino, Luigi, et al.
Published: (2026)

Language Agents Meet Causality -- Bridging LLMs and Causal World Models
by: Gkountouras, John, et al.
Published: (2024)

Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
by: Mohamed, Nazal, et al.
Published: (2026)

Better Decisions through the Right Causal World Model
by: Dillies, Elisabeth, et al.
Published: (2025)

A Quantile Regression Approach for Remaining Useful Life Estimation with State Space Models
by: Frizzo, Davide, et al.
Published: (2025)