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RankGLU: Residual Gated Score Formation for Cross-Sectional Stock Prediction
arXiv:2606.08930v1 Announce Type: new Abstract: Cross-sectional stock prediction is closer to a ranking problem than to ordinary return-magnitude regression, since portfolio decisions depend on the relative ordering of assets within each trading date. Existing temporal, graph-based, and market-conditioned attention models have improved stock representation learning, yet the final prediction head is often treated as a minor implementation detail. This paper argues that, under...
Modeling Nonlinear Feature Interactions with Product-Unit Residual Networks
arXiv:2606.06861v1 Announce Type: new Abstract: Understanding nonlinear feature interactions is crucial in science and engineering, yet standard multilayer perceptrons (MLPs) often capture such interactions only implicitly, leading to entangled representations that can impair robustness and interpretability. We investigate product-unit residual networks (PURe) that integrate multiplicative product units with residual connections to explicitly model cross-feature couplings while stabilizing...
DeRes: Decoupling Residual Stability and Adaptivity for Scalable CTR Prediction
arXiv:2606.07980v1 Announce Type: new Abstract: Transformer-based CTR models face a growing bottleneck at the residual connection: under Pre-Norm, early user-interest signals are diluted layer by layer; the identity skip cannot forget stale interests; and each layer sees only its immediate predecessor, losing long-range cross-layer dependencies. Recent attention-based residual variants (AttnRes) address parts of this in language models, but drop the protective identity skip and have not been...
ResCLIP: Residual Attention for Training-free Dense Vision-language Inference
Announce Type: replace Abstract: While vision-language models like CLIP have shown remarkable success in open-vocabulary tasks, their application is currently confined to image-level tasks, and they still struggle with dense predictions. Recent works often attribute such deficiency in dense predictions to the self-attention layers in the final block, and have achieved commendable results by modifying the original query-key attention to self-correlation attention, (e.g., query-query and...
Few-Shot Prediction for Pulsar Noise with Long Short-Term Memory Network
Announce Type: cross Abstract: This work proposes a novel solution to predict pulsar timing residuals with limited data, addressing the critical challenge of data scarcity across spin-frequency subgroups of millisecond pulsars in PTA datasets. The proposed solution applies a Long Short-Term Memory (LSTM) network optimized using the model-agnostic meta-learning algorithm, enabling rapid adaptation to new frequency domain by fine-tuning the LSTM network with only a few-shot of ground truth...
Error Amplification Limits ANN-to-SNN Conversion in Continuous Control
arXiv:2601.21778v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) can achieve competitive performance by converting already existing well-trained Artificial Neural Networks (ANNs), avoiding further costly training. This property is particularly attractive in Reinforcement Learning (RL), where training through environment interaction is expensive and potentially unsafe. However, existing conversion methods perform poorly in continuous control, where suitable baselines are...
Fasting Status and Epigenetic Clock Stability: Implications for Aging Research
Background: Epigenetic clocks are DNA methylation-based biomarkers increasingly used in aging research and clinical trials. A recent assessment of 18 clocks across multiple short-term perturbations concluded that most demonstrate only moderate biological reliability, raising concerns about their translational utility. However, understanding biological variability requires understanding the construction of each clock: different clocks capture distinct biological properties that respond...
Dynamic Gating Mechanism of the b0,+AT-Mediated Arg Transport: Insights from ASMD Simulations
Heteromeric amino acid transporters (HATs) mediate essential amino acid flux across membranes, but the molecular dynamics of substrate translocation remain poorly defined for many family members. Here, using conventional and adaptive steered molecular dynamics (cMD and ASMD) simulations, we identify residue W230 in the b0,+AT transport channel as a dynamic gate that regulates arginine (Arg) influx through side chain flipping. By integrating dynamic network analysis with dynamical...
On Improving Robustness of Deepfake Image Detectors
arXiv:2606.02797v1 Announce Type: new Abstract: The rapid advancement of Generative AI has introduced remarkable opportunities while simultaneously raising critical concerns regarding content authenticity. While recent work has increasingly focused on improving the generalization of deepfake detectors across unseen generative models, their robustness against adversarial attacks remains limited. In particular, Abdullah et al.
On Improving Robustness of Deepfake Image Detectors
arXiv:2606.02797v2 Announce Type: replace Abstract: The rapid advancement of Generative AI has introduced remarkable opportunities while simultaneously raising critical concerns regarding content authenticity. While recent work has increasingly focused on improving the generalization of deepfake detectors across unseen generative models, their robustness against adversarial attacks remains limited. In particular, Abdullah et al.