cs papers | Gist.Science

AI-Enabled Public Health Agent for SupportingFrontline Healthcare Workers in Primary CareSettings: Design, Evaluation, and Decision Support

This study presents and evaluates a lightweight, Retrieval-Augmented Generation (RAG)-based Public Health Agent that successfully enhances information retrieval, decision support, and operational efficiency for frontline healthcare workers in primary care settings while maintaining minimal computational overhead, though its clinical effectiveness requires further real-world validation.

Sayed Mohammed Zeeshan2026-06-30

💻 computer science

A parameter-efficient deep ensemble for automated flow cytometry-based diagnosis

The paper introduces CytoDNNEnsemble, a parameter-efficient deep ensemble model that leverages complementary global and local perspectives to automate high-dimensional flow cytometry analysis, achieving superior accuracy and robustness compared to state-of-the-art methods while minimizing reliance on expert gating.

Tomasz Gniazdowski, Urszula Markowska-Kaczmar2026-06-30

💻 computer science

Multi-Orientation Hybrid Convolutional Feature Learning for Touch-Less Face-Based Biometric Recognition

This study proposes an orientation-aware hybrid convolutional neural network that integrates hand-crafted edge and texture filters with deep learning features to enhance touch-less face recognition robustness against pose, illumination, and occlusion variations, achieving improved F1-scores across three benchmark datasets.

sulochana sonkamble, Balwant sonkamble2026-06-30✓ Author reviewed ⓘ

💻 computer science

How LLMs Audit Each Other: Five Mechanisms of Auditor Bias in Cross-Model Peer Review Under Identity Disclosure and Cross-Lingual Conditions

This paper investigates how identity disclosure and cross-lingual mismatches introduce five distinct bias mechanisms into LLM-to-LLM peer review, demonstrating through multi-model experiments that self-reported scores are unreliable indicators of auditor stability and necessitate independent qualitative analysis of justificatory text.

Evans F. Tovar O.2026-06-30

💻 computer science

Algorithmic Groupthink: Causal Analysis and Mitigation of Semantic Convergence in Multi-agent LLM Systems

This paper identifies and quantifies "Algorithmic Groupthink," a phenomenon where multi-agent LLM systems lose semantic diversity when sharing intermediate work, and demonstrates that this inference-time issue can be effectively mitigated through specific prompt-level instructions without compromising output quality.

Hideki Muto, Tetsuro Ogi, Takahiro Yakoh2026-06-30

💻 computer science

Cognitive Supply Chain Twins in Geopolitical Turbulence: A Multi-Agent Reinforcement Learning Architecture for Autonomous Resilience in Emerging Economies

This paper proposes a Cognitive Supply Chain Twin architecture integrating Digital Twins with Multi-Agent Reinforcement Learning to autonomously enhance supply chain resilience against geopolitical disruptions in emerging economies, demonstrating through simulations that this approach significantly outperforms traditional methods in maintaining operational continuity, reducing recovery time, and lowering costs within the specific context of Peru.

PAUL RICARDO PRUDENCIO GALVEZ2026-06-30

💻 computer science

QBK-ProtoNet: Quality-Calibrated Bio-Kinematic Covariance Prototype Learning for Deepfake Video Detection

This paper proposes QBK-ProtoNet, an interpretable deepfake detection framework that leverages quality-calibrated bio-kinematic covariance prototypes to robustly identify manipulated videos across degraded conditions and unseen domains by measuring physiological and temporal inconsistencies against learned authentic and manipulated evidence.

Sharon Philip, Shyamala Devi N2026-06-30

💻 computer science

The Neuron as a Latent State: Classical Variational Readout in Distributional Neural Units

This paper introduces EVE, a distributional neural unit that treats hidden states as local variational latents, and demonstrates through a posterior-freezing protocol that a non-oracle branch-medoid readout can effectively decode this latent state to improve multimodal forecasting accuracy and coverage without retraining.

Yves Ruffenach2026-06-30

💻 computer science

Predictive Intelligence for Civil Works Valuation: A Hybrid Random Forest–ANN Model with 91.20% Accuracy for Dynamic Cost Management in Peru

This study proposes a hybrid Random Forest–ANN model trained on 450 Peruvian construction projects that achieves 91.20% accuracy in dynamic cost valuation, significantly reducing prediction errors and geographic bias while offering a viable pathway for integration into Peru's public infrastructure management frameworks.

PAUL RICARDO PRUDENCIO GALVEZ2026-06-30

💻 computer science

Design of U-Net Architectures for Medical Image Segmentation using AI/ML Model

This paper reviews the evolution of U-Net architectures for medical image segmentation, highlighting their five principal variants, integration with advanced techniques like GANs and data augmentation, and optimizations for efficiency and transparency that collectively enhance accuracy and clinical applicability in disease diagnosis and treatment planning.

Pankaj Chandankhede2026-06-30

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