{"total":17,"rows":[{"id":"2403.08335","title":"A Sparsity Principle for Partially Observable Causal Representation Learning","created":"2024-03-13","cited_by_count":35,"area":null},{"id":"2406.05937","title":"Linear Causal Representation Learning from Unknown Multi-node Interventions","created":"2024-06-09","cited_by_count":14,"area":null},{"id":"2410.23620","title":"Identifiability Guarantees for Causal Disentanglement from Purely Observational Data","created":"2024-10-31","cited_by_count":7,"area":null},{"id":"2312.03580","title":"Invariance & Causal Representation Learning: Prospects and Limitations","created":"2023-12-06","cited_by_count":5,"area":null},{"id":"2502.20099","title":"Sanity Checking Causal Representation Learning on a Simple Real-World System","created":"2025-02-27","cited_by_count":5,"area":null},{"id":"2604.23800","title":"Causal Representation Learning from General Environments under Nonparametric Mixing","created":"2026-04-26","cited_by_count":5,"area":null},{"id":"2410.00535","title":"The Causal Information Bottleneck and Optimal Causal Variable Abstractions","created":"2024-10-01","cited_by_count":4,"area":null},{"id":"2603.08682","title":"Structural Causal Bottleneck Models","created":"2026-03-09","cited_by_count":4,"area":null},{"id":"2509.17784","title":"Revealing Multimodal Causality with Large Language Models","created":"2025-09-22","cited_by_count":3,"area":null},{"id":"2602.05033","title":"Causal Representation Meets Stochastic Modeling under Generic Geometry","created":"2026-02-04","cited_by_count":2,"area":null},{"id":"2604.23790","title":"A General Representation-Based Approach to Multi-Source Domain Adaptation","created":"2026-04-26","cited_by_count":2,"area":null},{"id":"2507.04754","title":"Intervening to Learn and Compose Causally Disentangled Representations","created":"2025-07-07","cited_by_count":1,"area":null},{"id":"2603.25796","title":"Beyond identifiability: Learning causal representations with few environments and finite samples","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2604.13218","title":"Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing","created":"2026-04-14","cited_by_count":1,"area":null},{"id":"2507.05412","title":"Incorporating Interventional Independence Improves Robustness against Interventional Distribution Shift","created":"2025-07-07","cited_by_count":0,"area":null},{"id":"2606.06288","title":"Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2608.28991","title":"Jigsaw-CRL: Recovering Global Latent Causal Order from Fragmented Multi-Client Interventions","created":"2026-08-29","cited_by_count":0,"area":null}],"next_cursor":null}