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arXiv:2603.05556v1 Announce Type: new Abstract: Integer sequences in the OEIS span values from single-digit constants to astronomical factorials and exponentials, making prediction challenging for standard …
arXiv:2603.05559v1 Announce Type: new Abstract: Decision makers exploiting photonic chaotic dynamics obtained by semiconductor lasers provide an ultrafast approach to solving multi-armed bandit problems by …
arXiv:2603.05566v1 Announce Type: new Abstract: Cross-modal alignment is a crucial task in multimodal learning aimed at achieving semantic consistency between vision and language. This requires …
arXiv:2603.05567v1 Announce Type: new Abstract: Dual-target structure-based drug design aims to generate a single ligand together with two pocket-specific binding poses, each compatible with a …
arXiv:2603.05573v1 Announce Type: new Abstract: Scalable sequence models, such as Transformer variants and structured state-space models, often trade expressivity power for sequence-level parallelism, which enables …
arXiv:2603.05579v1 Announce Type: new Abstract: Railcar shunting is a core planning task in freight railyards, where yard planners need to disassemble and reassemble groups of …
arXiv:2603.05582v1 Announce Type: new Abstract: The issue of algorithmic biases in deep learning has led to the development of various debiasing techniques, many of which …
arXiv:2603.05625v1 Announce Type: new Abstract: When used in automated decision-making systems, machine learning (ML) models are vulnerable to data-manipulation attacks. Some defense mechanisms (e.g., adversarial …
arXiv:2603.05671v1 Announce Type: new Abstract: Market valuations for professional athletes is a difficult problem, given the amount of variability in performance and location from year …
arXiv:2603.05673v1 Announce Type: new Abstract: The power flow equations are non-linear multivariate equations that describe the relationship between power injections and bus voltages of electric …
arXiv:2603.05691v1 Announce Type: new Abstract: It is increasingly common in machine learning to use learned models to label data and then employ such data to …
arXiv:2603.05694v1 Announce Type: new Abstract: We prove that Moore machines can be exactly realized as state-space models (SSMs), establishing a formal correspondence between symbolic automata …