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cs.LG2026
Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments
Andrea Rubbi, Arpit Merchant, Samuel Ogden +4
High-throughput gene perturbation experiments can test several genetic interventions in parallel, yet experimental budgets remain limited. A central goal is hit discovery: identify…
cs.LG2026
Shortest-Path Flow Matching with Mixture-Conditioned Bases for OOD Generalization to Unseen Conditions
Andrea Rubbi, Amir Akbarnejad, Mohammad Vali Sanian +10
Robust generalization under distribution shift remains a key challenge for conditional generative modeling: conditional flow-based methods often fit the training conditions well bu…
cs.LG2026
DirMoE: Dirichlet-routed Mixture of Experts
Amirhossein Vahidi, Hesam Asadollahzadeh, Navid Akhavan Attar +4
Mixture-of-Experts (MoE) models have demonstrated exceptional performance in large-scale language models. Existing routers typically rely on non-differentiable Top-+Softmax, lim…