AINeutralarXiv – CS AI · 6h ago6/10
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Modularity-Free Conflict-Averse Training for Generalized PINNs
Researchers identify a critical failure mode in Physics-Informed Neural Networks (PINNs) where overparameterized models self-partition into task-exclusive modules that impede training convergence. They introduce ModSync, a novel framework combining structural optimization with conflict-averse training to prevent capacity-driven failures and achieve state-of-the-art accuracy across PDE benchmarks.