Image de couverture de livre

Emerging Synergies in Causality and Deep Generative Models: A Survey

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhou, Guanglin, Xie, Shaoan, Hao, Guang-Yuan, Chen, Shiming, Huang, Biwei, Xu, Xiwei, Wang, Chen, Zhu, Liming, Yao, Lina, Zhang, Kun
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization
par: Zhou, Guanglin, et autres
Publié: (2024)

Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning
par: Zhou, Guanglin, et autres
Publié: (2024)

Retrieval-Augmented Review Generation for Poisoning Recommender Systems
par: Yang, Shiyi, et autres
Publié: (2025)

Review-Incorporated Model-Agnostic Profile Injection Attacks on Recommender Systems
par: Yang, Shiyi, et autres
Publié: (2024)

Advancing Counterfactual Inference through Nonlinear Quantile Regression
par: Xie, Shaoan, et autres
Publié: (2023)

Causal Representation Learning from Multiple Distributions: A General Setting
par: Zhang, Kun, et autres
Publié: (2024)

Differentiable Causal Discovery For Latent Hierarchical Causal Models
par: Prashant, Parjanya, et autres
Publié: (2024)

Causal Representation Learning from General Environments under Nonparametric Mixing
par: Ng, Ignavier, et autres
Publié: (2026)

Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality
par: Kong, Lingjing, et autres
Publié: (2025)

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
par: Xie, Feng, et autres
Publié: (2023)

Natural Counterfactuals With Necessary Backtracking
par: Hao, Guang-Yuan, et autres
Publié: (2024)

Learning by Analogy: A Causal Framework for Composition Generalization
par: Kong, Lingjing, et autres
Publié: (2025)

Causal Representation Meets Stochastic Modeling under Generic Geometry
par: Ren, Jiaxu, et autres
Publié: (2026)

Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
par: Li, Zijian, et autres
Publié: (2025)

DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents
par: Yang, Shiyi, et autres
Publié: (2025)

Nonparametric Identification of Latent Concepts
par: Zheng, Yujia, et autres
Publié: (2025)

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
par: Wang, Xinyue, et autres
Publié: (2025)

A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model
par: Zhou, Jingwen, et autres
Publié: (2024)

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation
par: Li, Yan, et autres
Publié: (2026)

Firm theories in neoclassical institutional economics
par: Shaoan Huang
Publié: (2024)

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
par: Fu, Minghao, et autres
Publié: (2025)

Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agents
par: Lu, Qinghua, et autres
Publié: (2023)

Planner Matters! An Efficient and Unbalanced Multi-agent Collaboration Framework for Long-horizon Planning
par: Wu, Wenyi, et autres
Publié: (2026)

A Reference Architecture for Designing Foundation Model based Systems
par: Lu, Qinghua, et autres
Publié: (2023)

Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks
par: Jin, Songyao, et autres
Publié: (2025)

Knowledge Graph Embeddings: A Comprehensive Survey on Capturing Relation Properties
par: Niu, Guanglin
Publié: (2024)

A Fast Kernel-based Conditional Independence test with Application to Causal Discovery
par: Schacht, Oliver, et autres
Publié: (2025)

Mutually Causal Semantic Distillation Network for Zero-Shot Learning
par: Chen, Shiming, et autres
Publié: (2026)

Causal-learn: Causal Discovery in Python
par: Zheng, Yujia, et autres
Publié: (2023)

Foundation Models for Environmental Science: A Survey of Emerging Frontiers
par: Yu, Runlong, et autres
Publié: (2025)

Transformer Is Inherently a Causal Learner
par: Wang, Xinyue, et autres
Publié: (2026)

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines
par: Xu, Xiwei, et autres
Publié: (2025)

Towards General Continuous Memory for Vision-Language Models
par: Wu, Wenyi, et autres
Publié: (2025)

HydraRAG: Structured Cross-Source Enhanced Large Language Model Reasoning
par: Tan, Xingyu, et autres
Publié: (2025)

Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge
par: Yang, Yupei, et autres
Publié: (2024)

MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning
par: Tan, Xingyu, et autres
Publié: (2025)

Federated Causal Discovery from Heterogeneous Data
par: Li, Loka, et autres
Publié: (2024)

SEDGE: Structural Extrapolated Data Generation
par: Zhang, Kun, et autres
Publié: (2026)

Controllable Video Generation with Provable Disentanglement
par: Shen, Yifan, et autres
Publié: (2025)

Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models
par: Zhang, Yuzhe, et autres
Publié: (2024)