cs papers | Gist.Science

A Dynamic Explainable AI FrameworkforReal-Time Intrusion Detection andAutomatedAlert Prioritization in Security OperationCenters

This paper proposes the Dynamic Explainable Framework (DEF), a three-stage pipeline integrating time-series Transformers, Graph Convolutional Networks, and post-hoc explainability techniques to achieve high-accuracy intrusion detection, significantly reduce analyst alert fatigue by prioritizing critical incidents, and provide transparent, near-real-time rationales for Security Operation Center environments.

Muhammad Usama Nazir, Asri Bin Ngadi2026-06-24

💻 computer science

SPQ-DETR for Tiny-UAV Detection]{SPQ-DETR: Prior-Guided Queries and Shape-Aware Geometric Supervision for Long-Range Tiny-UAV Detection

This paper proposes SPQ-DETR, a transformer-based detector that enhances long-range tiny-UAV detection by integrating high-resolution feature preservation, prior-guided queries initialized from encoder tokens, and shape-aware geometric supervision to significantly improve accuracy and recall on challenging datasets.

Guangshuo Zhang, Yunpeng Hu, Ying He, Teng Yu2026-06-24

💻 computer science

Verified Self-Improving Learning of Large Language Models for Multi-Objective Point-Spec Circuit Design

This paper introduces \methodfull, a simulation-driven self-improving framework that iteratively generates, verifies, and repairs circuit netlists using Pareto-Verified Preference Optimization and Safe Proximal Policy Optimization to achieve high-precision, multi-objective point-spec circuit design across diverse analog families.

Juzheng Zhang, Kehao Zhang, Jinwen Liu, Yangfan Tang, Lijuan Li, Hongliang Liu, You Chen2026-06-24

💻 computer science

Learning Latent Neural Signatures from EEG Scalograms for Robust Biometric Identification

This paper proposes a robust EEG-based biometric identification system that converts 64-channel signals into 2D latent neural signatures via wavelet scalograms and a convolutional autoencoder, then classifies subjects using a custom ResNet to achieve 99.1% accuracy on the PhysioNet Motor Imagery dataset.

T. Sameer, R. V. M. Deekshith, P. Karthik, Peeta Basa Pati, Debanjali Bhattacharya2026-06-24

💻 computer science

Enhancing Audio Feature Extraction viaReservoir Convolution

This paper proposes two Reservoir Computing-based architectural modifications that replace traditional, computationally complex MFCC feature extraction with efficient time-domain convolutions, achieving superior performance in speech recognition tasks through either a decentralized multi-reservoir ensemble or a single composite waveform approach.

Rinku Sebastian, Prof. Simon O'Keefe, Prof. Martin Trefzer2026-06-24

💻 computer science

Personified Images of ChatGPT and Gemini: Exploring Representations of Functional Identity Through Reverse Correlation

This study utilizes reverse-correlation methods to demonstrate that multimodal LLMs like ChatGPT and Gemini generate stable, self-recognizing, and positively valenced "personified" facial images, providing preliminary evidence that these models may possess internal representations of their functional identity.

Chanhee Bae, Jeongyeon Jung, Donghee Kang, Hyeji Kang, Seunghyun Kim, Kayoung Lee, Yeonjae Lee, Seohyeon Mun, Young-gun (…)2026-06-24

💻 computer science

Artificial Intelligence-Based Optimal Classifier for the Prediction of Heart Ailment

This study demonstrates that a Support Vector Machine (SVM) classifier, optimized using eight key features selected from the Cleveland dataset, achieves superior performance with 90.28% accuracy and a 93% AUC in predicting heart ailments compared to thirty other classifiers.

Sagar Singh Rathore, Amit Garg, Vijay Kumar Soni, Khemraj Deshmukh, Roshni Rathour2026-06-24✓ Author reviewed ⓘ

💻 computer science

Lessons Learned and Iterative Enhancements: A 2-Year Experience with an Established Responsible AI Framework

Over a two-year period, UNC Health enhanced its Responsible AI framework by implementing a three-tier risk-based system that significantly improved evaluation efficiency and reduced lead times while maintaining rigorous oversight, resulting in the successful review of 64 solutions and the establishment of robust post-deployment monitoring mechanisms with minimal adverse events.

Torre Caparatta, Ada H. Tsoi, Darius K. Byramji, Shahryar Farooq, Kathryn Ruiz, Cassiopeia Frank, Gary Gartner, Noah Sch (…)2026-06-24

💻 computer science

When Does a Partitioned ANN Index Need Active Re-Partitioning Under Drift? A Characterization and Benchmark

This paper challenges the premise that active re-partitioning is universally necessary for vector-search indices under data drift, demonstrating through controlled benchmarks that static partitions suffice for moderate turnover while revealing that incremental re-centering is the cost-effective solution for significant distribution shifts, ultimately providing a regime map and decision rule for practitioners to determine when maintenance is truly required.

Jaswin Jose2026-06-24

💻 computer science

Learning Safe Multi-Robot Coordination in Industrial Cyber- Physical Systems

This paper presents a multi-agent reinforcement learning framework for safe industrial robot coordination, demonstrating through simulation that while a deterministic greedy baseline outperforms the proposed safe MARL policy in efficiency, the latter enables emergent communication patterns and highlights the critical need for adaptive communication bandwidth to mitigate collision risks as fleet sizes scale.

Bernard Kyiewu, Clinton Amponsah, Linda Bessa-Simons, Andrew Oppong-Asante, Caleb Boakye Yiadom2026-06-24

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