arXiv:2607.19170v1 Announce Type: new Abstract: Functional magnetic resonance imaging (fMRI)-based visual decoding aims to recover visual information from measured brain activity, commonly by mapping fMRI responses…
arXiv:2607.18412v1 Announce Type: cross Abstract: Dynamic graph learning aims to capture evolving structural and semantic patterns in real-world systems, such as fraud detection and recommender systems.…
arXiv:2607.18574v1 Announce Type: cross Abstract: Direct feedback alignment (DFA) trains hidden layers with fixed random projections of the output error, avoiding the transposed-weight backward pass of…
arXiv:2607.18969v1 Announce Type: cross Abstract: A walking fly steers toward a goal direction, held as a bump of activity across the FC2 neurons of the fan-shaped…
arXiv:2511.08436v2 Announce Type: replace Abstract: How complex collective behavior emerges from individual interactions is a fundamental scientific question, but experimental cost and difficulty of simultaneous multi-brain…
arXiv:2607.19090v1 Announce Type: cross Abstract: Chemistry describes aspects of the universe in terms of molecules and their reactions. In this exploratory work we present a way…
arXiv:2602.10552v3 Announce Type: replace Abstract: Whereas most brain-computer interface research has focused on decoding neural signals into behavior or intent, the reverse challenge-using controlled stimuli to…
arXiv:2602.18948v2 Announce Type: replace-cross Abstract: Transformer models contain substantial internal redundancy arising from coordinate-dependent representations and continuous symmetries, in model space and in head space, respectively.…
arXiv:2604.09026v3 Announce Type: replace-cross Abstract: Social agents both internalize collective norms and reshape them through creative action, yet computational models have not captured this bidirectional process…
arXiv:2603.09793v2 Announce Type: replace Abstract: Bayesian optimization is a data-efficient technique that has been shown to be extremely powerful to optimize expensive, black-box, and possibly noisy…
arXiv:2607.18292v1 Announce Type: new Abstract: As language models scale, answers start truer but degrade faster: scaling buys capability but erodes reliability. The knowledge-gap account - more…
arXiv:2507.06445v3 Announce Type: replace Abstract: Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input data? We propose…
arXiv:2607.18291v1 Announce Type: new Abstract: Time-dependent reliability analysis is crucial for ensuring the long-term safety and performance of engineering systems under uncertainties. However, traditional surrogate model…
arXiv:2607.19167v1 Announce Type: cross Abstract: Motivated by the numerical computation of the Mean Escape Time (MET) $tau:Omegatomathbb{R}$ of a stochastic process from a bounded domain $Omegasubseteqmathbb{R}^d$,…
arXiv:2607.18290v1 Announce Type: new Abstract: In recent years, Kolmogorov-Arnold Networks (KANs) have attracted increasing attention due to their effectiveness in machine learning and scientific computing tasks,…
arXiv:2607.18652v1 Announce Type: cross Abstract: We establish a $widetildeOmega(d^{5/4}sqrt T)$ lower bound on the minimax expected regret of stochastic bandit convex optimization of $1$-Lipschitz functions on…
arXiv:2607.18289v1 Announce Type: new Abstract: Continual anomaly detection (CAD) studies how models can adapt to evolving data distributions while retaining performance on previously observed regimes. CAD…
arXiv:2607.10248v2 Announce Type: replace-cross Abstract: Language builds discourse contexts other than the actual: a painting, a belief, a memory, a hypothetical. Each is a mental space…
arXiv:2607.18288v1 Announce Type: new Abstract: Load imbalance across edge and cloud layers degrades latency performance in hierarchical edge-cloud computing (HECC) systems under dynamic task arrivals and…
arXiv:2604.26182v2 Announce Type: replace-cross Abstract: World models of embodied agents predict future observations conditioned on an action taken by the agent. For complex embodiments, action spaces…
arXiv:2607.18280v1 Announce Type: new Abstract: Large language models (LLMs) are often compressed through static parameter pruning or dynamic token-level computation, yet aggressive sparsification can trigger rapid…
arXiv:2607.18282v1 Announce Type: new Abstract: Bayesian Optimization is widely used for expensive black-box optimization, yet its success often depends on choosing a kernel that matches the…
arXiv:2607.18283v1 Announce Type: new Abstract: Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnormalities.…
arXiv:2607.18285v1 Announce Type: new Abstract: We present E-SpecFormer (Edge Spectrum monitoring Transformer) for end-to-end automatic modulation and covert channel (CC) recognition. We introduce LiTAN (Linear Tanh…