Copertina

FACTS: A Factored State-Space Framework For World Modelling

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Nanbo, Li, Laakom, Firas, Xu, Yucheng, Wang, Wenyi, Schmidhuber, Jürgen
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
di: Laakom, Firas, et al.
Pubblicazione: (2025)

PhysGym: Benchmarking LLMs in Interactive Physics Discovery with Controlled Priors
di: Chen, Yimeng, et al.
Pubblicazione: (2025)

Huxley-Gödel Machine: Human-Level Coding Agent Development by an Approximation of the Optimal Self-Improving Machine
di: Wang, Wenyi, et al.
Pubblicazione: (2025)

Planning to Explore: Curiosity-Driven Planning for LLM Test Generation
di: Amayuelas, Alfonso, et al.
Pubblicazione: (2026)

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

Language Agents as Optimizable Graphs
di: Zhuge, Mingchen, et al.
Pubblicazione: (2024)

Highway Value Iteration Networks
di: Wang, Yuhui, et al.
Pubblicazione: (2024)

Interestingness as an Inductive Heuristic for Future Compression Progress
di: Herrmann, Vincent, et al.
Pubblicazione: (2026)

Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
di: Ramesh, Aditya A., et al.
Pubblicazione: (2024)

Torch-Uncertainty: A Deep Learning Framework for Uncertainty Quantification
di: Lafage, Adrien, et al.
Pubblicazione: (2025)

Class-wise Generalization Error: an Information-Theoretic Analysis
di: Laakom, Firas, et al.
Pubblicazione: (2024)

State Space Models over Directed Graphs
di: She, Junzhi, et al.
Pubblicazione: (2025)

Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search
di: Andronov, Mikhail, et al.
Pubblicazione: (2025)

Explaining Fine Tuned LLMs via Counterfactuals A Knowledge Graph Driven Framework
di: Wang, Yucheng, et al.
Pubblicazione: (2025)

Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
di: Bayram, Firas, et al.
Pubblicazione: (2024)

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration
di: Chen, Xingsheng, et al.
Pubblicazione: (2026)

How Many Heads Make an SSM? A Unified Framework for Attention and State Space Models
di: Ghodsi, Ali
Pubblicazione: (2025)

Decoupling the "What" and "Where" With Polar Coordinate Positional Embeddings
di: Gopalakrishnan, Anand, et al.
Pubblicazione: (2025)

Chemical Language Models for Natural Products: A State-Space Model Approach
di: Wang, Ho-Hsuan, et al.
Pubblicazione: (2026)

State Space Models on Temporal Graphs: A First-Principles Study
di: Li, Jintang, et al.
Pubblicazione: (2024)

Seasonal Forecasting of Pan-Arctic Sea Ice with State Space Model
di: Wang, Wei, et al.
Pubblicazione: (2025)

Understanding World or Predicting Future? A Comprehensive Survey of World Models
di: Ding, Jingtao, et al.
Pubblicazione: (2024)

STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model
di: Li, Lincan, et al.
Pubblicazione: (2024)

GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
di: Fu, Yali, et al.
Pubblicazione: (2025)

Highway Reinforcement Learning
di: Wang, Yuhui, et al.
Pubblicazione: (2024)

Exploring Adversarial Robustness of Deep State Space Models
di: Qi, Biqing, et al.
Pubblicazione: (2024)

Recognizing Dementia from Neuropsychological Tests with State Space Models
di: Wang, Liming, et al.
Pubblicazione: (2025)

HealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction
di: Yu, Dahai, et al.
Pubblicazione: (2026)

Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection
di: Zhan, Zheng, et al.
Pubblicazione: (2025)

ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data
di: Wang, Jiangyuan, et al.
Pubblicazione: (2026)

Chimera: State Space Models Beyond Sequences
di: Lahoti, Aakash, et al.
Pubblicazione: (2025)

Efficient State Space Model via Fast Tensor Convolution and Block Diagonalization
di: Liang, Tongyi, et al.
Pubblicazione: (2024)

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
di: Chen, Junqi, et al.
Pubblicazione: (2024)

Accelerating the inference of string generation-based chemical reaction models for industrial applications
di: Andronov, Mikhail, et al.
Pubblicazione: (2024)

Puppet-CNN: Continuous Parameter Dynamics for Input-Adaptive Convolutional Networks
di: Xing, Yucheng, et al.
Pubblicazione: (2024)

Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
di: Wang, Chloe, et al.
Pubblicazione: (2024)

SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
di: Gao, Hongfan, et al.
Pubblicazione: (2024)

Mamba State-Space Models Are Lyapunov-Stable Learners
di: Halloran, John T., et al.
Pubblicazione: (2024)

Uncovering the Spectral Bias in Diagonal State Space Models
di: Solozabal, Ruben, et al.
Pubblicazione: (2025)

Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
di: Terzić, Aleksandar, et al.
Pubblicazione: (2025)