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Incorporating contextual information into KGWAS for interpretable GWAS discovery

arXiv:2603.25855v1 Announce Type: new Abstract: Genome-Wide Association Studies (GWAS) identify associations between genetic variants and disease; however, moving beyond associations to causal mechanisms is critical for therapeutic target prioritization. The recently proposed Knowledge Graph GWAS (KGWAS) framework addresses this challenge…

Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models

arXiv:2503.22886v2 Announce Type: replace Abstract: Recent advancements in imitation learning have led to transformer-based behavior foundation models (BFMs) that enable multi-modal, human-like control for humanoid agents. While excelling at zero-shot generation of robust behaviors, BFMs often require meticulous prompt engineering…

A Compression Perspective on Simplicity Bias

arXiv:2603.25839v1 Announce Type: new Abstract: Deep neural networks exhibit a simplicity bias, a well-documented tendency to favor simple functions over complex ones. In this work, we cast new light on this phenomenon through the lens of the Minimum Description Length…

On the Objective and Feature Weights of Minkowski Weighted k-Means

arXiv:2603.25958v1 Announce Type: new Abstract: The Minkowski weighted k-means (mwk-means) algorithm extends classical k-means by incorporating feature weights and a Minkowski distance. Despite its empirical success, its theoretical properties remain insufficiently understood. We show that the mwk-means objective can be…