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arXiv:2603.11117v1 Announce Type: new Abstract: Tree-based models are widely recognized for their interpretability and have proven effective in various application domains, particularly in high-stakes domains. …
arXiv:2603.11118v1 Announce Type: new Abstract: The superposition of arrival processes is a fundamental yet analytically intractable operation in queueing networks when inputs are general non-renewal …
arXiv:2603.11119v1 Announce Type: new Abstract: Electroencephalography(EEG)-basedemotionrecognitionre- mains challenging in cross-subject settings due to severe inter-subject variability. Existing methods mainly learn subject-invariant features, but often under-exploit …
arXiv:2603.11121v1 Announce Type: new Abstract: Building design optimization often depends on physics-based simulation tools such as EnergyPlus, which, although accurate, are computationally expensive and slow. …
arXiv:2603.11131v1 Announce Type: new Abstract: While Quantum Convolutional Neural Networks (QCNNs) offer a theoretical paradigm for quantum machine learning, their practical implementation is severely bottlenecked …
arXiv:2603.11133v1 Announce Type: new Abstract: Transformer self-attention computes pairwise token interactions, yet protein sequence to phenotype relationships often involve cooperative dependencies among three or more …
arXiv:2603.11137v1 Announce Type: new Abstract: On-policy distillation is pivotal for transferring reasoning capabilities to capacity-constrained models, yet remains prone to instability and negative transfer. We …
arXiv:2603.11139v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong code generation abilities in general-purpose programming languages but remain limited in specialized domains such …
arXiv:2603.11140v1 Announce Type: new Abstract: Fairness in machine learning research has largely focused on outcome-oriented fairness criteria such as Equalized Odds, while comparatively less attention …
arXiv:2603.11142v1 Announce Type: new Abstract: The paper explores how video models trained for classification tasks represent nuanced, hidden semantic information that may not affect the …
arXiv:2603.11149v1 Announce Type: new Abstract: Large language models remain vulnerable to jailbreak attacks, yet we still lack a systematic understanding of how jailbreak success scales …
arXiv:2603.11161v1 Announce Type: new Abstract: We formally define Algorithmic Capture (i.e., ``grokking'' an algorithm) as the ability of a neural network to generalize to arbitrary …