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cs.LG2026
A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation
Yan Li, Yuewen Sun, Shaoan Xie +4
Causal representation learning (CRL) and traditional representation learning have largely developed along different trajectories. Traditional representation learning has been drive…
cs.LG2025
CausalVerse: Benchmarking Causal Representation Learning with Configurable High-Fidelity Simulations
Guangyi Chen, Yunlong Deng, Peiyuan Zhu +4
Causal Representation Learning (CRL) aims to uncover the data-generating process and identify the underlying causal variables and relations, whose evaluation remains inherently cha…
cs.LG2025
Should Bias be Eliminated? A General Framework to Use Bias for OOD Generalization
Yan Li, Yunlong Deng, Zijian Li +4
Most approaches to out-of-distribution (OOD) generalization learn domain-invariant representations by discarding contextual bias. In this paper, we raise a critical question: Shoul…