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cs.LG2026
CausalVAE as a Plug-in for World Models: Towards Reliable Counterfactual Dynamics
Ziyi Ding, Xianxin Lai, Weiyu Chen +2
In this work, CausalVAE is introduced as a plug-in structural module for latent world models and is attached to diverse encoder-transition backbones. Across the reported benchmarks…
cs.LG2026
Step-by-Step Causality: Transparent Causal Discovery with Multi-Agent Tree-Query and Adversarial Confidence Estimation
Ziyi Ding, Chenfei Ye-Hao, Zheyuan Wang +1
Causal discovery aims to recover ``what causes what'', but classical constraint-based methods (e.g., PC, FCI) suffer from error propagation, and recent LLM-based causal oracles oft…
cs.LG2025
GaussDetect-LiNGAM:Causal Direction Identification without Gaussianity test
Ziyi Ding, Xiao-Ping Zhang
We propose GaussDetect-LiNGAM, a novel approach for bivariate causal discovery that eliminates the need for explicit Gaussianity tests by leveraging a fundamental equivalence betwe…