cs papers | Gist.Science

A Validated Measurement Protocol for Comparable, Cost-Aware Software Testing Evaluation: A Reproducible Benchmark, an Oracle Sampling-Budget Guarantee, and a Real-Fault Validity Study, Instantiated for Quantum Programs

This paper introduces a validated, reproducible measurement protocol (QSQ-Bench and Q-EVAL) that ensures comparable, cost-aware, and construct-valid software testing evaluations by establishing statistical oracle guarantees and demonstrating its effectiveness through a comprehensive study on quantum programs and a classical system.

Bhanwar Gupta, Sanjeev Rana2026-08-26

💻 computer science

SFE-YOLO: Spatial-Frequency Dual-Domain Enhanced YOLO for SAR Ship Detection

To address the limitations of existing detectors in complex marine environments, the paper proposes SFE-YOLO, a dual-domain enhanced YOLO framework that integrates pinwheel convolution for multi-orientation feature extraction and a frequency-domain block for sea clutter suppression, achieving superior performance in SAR ship detection on SSDD and HRSID datasets.

Huicong Ning, Ying Zhang, Jiajia Chen, Peinan Hao, Xiaojing Zhao, Tianzi Yan2026-08-26

💻 computer science

Context-Aware LLM Evaluators for Content Moderation Judgments in a Low-Resource Setting

This study demonstrates that while context-aware prompting and retrieval of prior decisions can improve Large Language Model evaluators for German newspaper forum moderation, the choice of model capacity is more critical than the prompting strategy, with the largest model outperforming supervised systems on rare removal categories without requiring annotated training data.

Felix Krejca, Tobias Kietreiber, Michael Wiegand, Sebastian Neumaier2026-08-26

💻 computer science

A Priority-Guided Action-Masked Proximal Policy Optimization Framework for Dynamic Scheduling of Electric Power Material Verification Tasks

This paper proposes PPO-TS, a priority-guided action-masked Proximal Policy Optimization framework that demonstrates a statistically significant improvement in a synthetic benchmark for dynamic electric power material verification scheduling, despite revealing limitations in equipment utilization and generalization boundaries.

Zhaolei He, Ao He, Cong Lin, Jing Zhao, Liping Gao, Xiang Yin2026-08-26

💻 computer science

Learning efficient representations of complex constraints for scalable optimization

The paper introduces PolyFormer, a physics-informed machine learning framework that learns compact polytopic representations of complex constraints to enable scalable, rapid, and accurate prescriptive optimization across diverse real-world problems.

Bo Zhao, Yilin Wen, Yi Guo, Wei Qi, Zechun Hu, Colin Jones, Jian Sun2026-08-26

💻 computer science

JarifNet: An Attention-Augmented Lightweight CNN for Highly Calibrated Edge Image Classification

This paper introduces JarifNet, a lightweight CNN architecture that combines inverted residual bottlenecks, Squeeze-and-Excitation attention, and Stochastic Depth to achieve state-of-the-art accuracy, probability calibration, and computational efficiency for edge image classification on the CIFAR-10 dataset.

Sadik Al Jarif2026-08-26

💻 computer science

TITAN: A Diversity-Driven Stacked Ensemble with a Multi-Branch Neural Network for Predicting Live Birth in IVF

The paper introduces TITAN, a diversity-driven stacked ensemble model that integrates five tree-based learners and a custom multi-branch neural network with rigorous leakage detection and Bayesian optimization to achieve state-of-the-art accuracy in predicting live birth outcomes for IVF cycles using the HFEA registry.

Bala Shiwangi¹, Shailesh D. Kamble², Brijesh Kumar¹2026-08-26

💻 computer science

Multi-classification of Brain Tumor MRI images using Convoluted Neural Network (CNN) based approach

This study proposes a custom seven-layer Convolutional Neural Network (CNN) model that achieves 96.10% test accuracy in classifying brain MRI images into Glioma, Meningioma, Pituitary, and normal categories, demonstrating robust performance for computer-aided diagnosis without relying on pre-trained models.

Bhavak Bajaj, PRIYA GOEL, Rajni Bala2026-08-26

💻 computer science

Construction of a Personalized Physical Fitness Training Recommendation System Based on Random Forest and Gradient Boosting Machine

This paper proposes a Domain-Knowledge-Driven Hierarchical Collaborative Learning (DKHCL) framework that integrates Random Forest feature selection with Gradient Boosting Machine prediction and Acute-Chronic Workload Ratio constraints to achieve high-accuracy personalized physical fitness recommendations, demonstrating both superior offline performance against advanced baselines and significant real-world improvements in injury reduction and goal-achievement efficiency in a prospective field validation.

Fuliang Geng, Mei Wei2026-08-26

💻 computer science

Enhanced EA-Transformer for Power Load Data Completion

This paper proposes an Enhanced EA-Transformer model that integrates a dual-baseline pre-filling strategy, a dynamically decaying evolutionary algorithm, and a multi-dimensional weighted loss function to achieve high-precision completion of missing power load time-series data under various missing mechanisms and rates.

Chao Li, Yiyang meng, Ji Li, Yuzheng Liu, Changlong Lv2026-08-26

← Previous Next →