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stat.ML2025
IndiSeek learns information-guided disentangled representations
Yu Gui, Cong Ma, Zongming Ma
Learning disentangled representations is a fundamental task in multi-modal learning. In modern applications such as single-cell multi-omics, both shared and modality-specific featu…
stat.ML2025
Multi-modal contrastive learning adapts to intrinsic dimensions of shared latent variables
Yu Gui, Cong Ma, Zongming Ma
Multi-modal contrastive learning as a self-supervised representation learning technique has achieved great success in foundation model training, such as CLIP~\citep{radford2021lear…
stat.ML2024
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
Yu Gui, Ying Jin, Zhimei Ren
Before deploying outputs from foundation models in high-stakes tasks, it is imperative to ensure that they align with human values. For instance, in radiology report generation, re…