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NES: An Instruction-Free, Low-Latency Next Edit Suggestion Framework Powered by Learned Historical Editing Trajectories
arXiv:2508.02473v3 Announce Type: replace-cross Abstract: Code editing is a frequent yet cognitively demanding task in software development. Existing AI-powered tools often disrupt developer flow by requiring explicit natural language instructions and suffer from high latency, limiting real-world usability. We present…
Mousse: Rectifying the Geometry of Muon with Curvature-Aware Preconditioning
arXiv:2603.09697v2 Announce Type: replace Abstract: Recent advances in spectral optimization, notably Muon, have demonstrated that constraining update steps to the Stiefel manifold can significantly accelerate training and improve generalization. However, Muon implicitly assumes an isotropic optimization landscape, enforcing a uniform…
CHEEM: Continual Learning by Reuse, New, Adapt and Skip — A Hierarchical Exploration-Exploitation Approach
arXiv:2303.08250v5 Announce Type: replace-cross Abstract: To effectively manage the complexities of real-world dynamic environments, continual learning must incrementally acquire, update, and accumulate knowledge from a stream of tasks of different nature without suffering from catastrophic forgetting of prior knowledge. While…
SetONet: A Set-Based Operator Network for Solving PDEs with Variable-Input Sampling
arXiv:2505.04738v3 Announce Type: replace Abstract: Most neural-operator surrogates for PDEs inherit from DeepONet-style formulations the requirement that the input function be sampled at a fixed, ordered set of sensors. This assumption limits applicability to problems with variable sensor layouts, missing…
Beyond Spectral Clustering: Probabilistic Cuts for Differentiable Graph Partitioning
arXiv:2511.02272v3 Announce Type: replace Abstract: Probabilistic relaxations of graph cuts offer a differentiable alternative to spectral clustering, enabling end-to-end and online learning without eigendecompositions, yet prior work centered on RatioCut and lacked general guarantees and principled gradients. We present a…