cs papers | Gist.Science

H. Dilpriya's Momentum (HDM) : A Multi-Strategy Gradient-Aligned Optimizer with Adaptive Per-Parameter Corrections, Cosine-Annealed Scheduling, and Convergence Guarantees for Deep Neural Networks

This paper introduces H. Dilpriya's Momentum (HDM), a novel multi-strategy optimizer that combines adaptive per-parameter corrections with cosine-annealed scheduling to achieve rigorous convergence guarantees and state-of-the-art gradient alignment, demonstrating superior performance on both ill-conditioned synthetic problems and deep learning benchmarks like MNIST and CIFAR-10.

Janaka Ishan Senarathna2026-07-13

💻 computer science

Multi-Tenant Edge-Cloud Hybrid LLM Serving using Speculative Decoding and Quantization

This paper proposes a multi-tenant edge-cloud hybrid LLM serving architecture that combines W4A16-quantized speculative decoding with asynchronous communication and a multi-tenant verification orchestrator to simultaneously address privacy, latency, and resource utilization challenges.

Jui-Yu Lin2026-07-13

💻 computer science

Learning Safe Behaviour via Justified Human Preferences and Hypothetical Queries

This paper introduces JPAL-HA, a safe learning model for safety-critical environments that leverages human action justifications to generate hypothetical queries, thereby significantly improving safety and sample efficiency while reducing human training burden.

Ilias Kazantzidis, Timothy J. Norman, Yali Du, Christopher T. Freeman2026-07-13

💻 computer science

Understanding Behavioural Risk Signals in Socio-Technical Work Systems Using Explainable Machine Learning

This study demonstrates that using explainable machine learning to analyze item-level safety climate data reveals nonlinear, threshold-dependent behavioural risk patterns driven by management responsiveness, training, and experience, challenging traditional linear aggregation models and offering a more precise basis for proactive accident prevention.

Omid Akbarzadeh, Parisa Moshashaei, Rasoul Ahmadpour, Mohammed Qadir Ali, Seyed Shamseddin Alizadeh2026-07-13

💻 computer science

ℓ0-Regularized Quadratic Surface Support Vector Machines

This paper proposes a sparse ℓ0-regularized quadratic surface support vector machine (QSVM) to address overfitting and interpretability issues in kernel-free nonlinear classification, introducing a penalty decomposition algorithm with provable optimality and convergence guarantees that demonstrates competitive performance and sparsity on both benchmark and real-world credit datasets.

Ahmad Mousavi, Ramin Zandvakili, Zheming Gao2026-07-13

💻 computer science

AI-Driven Multimodal Communication Framework for Inclusive Classrooms: A PRISMA-Based Systematic Review for Deaf Learners

This paper presents a PRISMA-based systematic review revealing the limitations of current auditory-centric solutions for deaf learners and proposes an AI-driven multimodal communication framework integrating speech recognition, natural language processing, and sign language generation to enable real-time visual support and achieve meaningful inclusion in classrooms.

shahir vk2026-07-13

💻 computer science

Empty scaffold allocation bias in molecular distribution shift evaluation

This paper reveals that standard scaffold-based evaluation methods introduce a hidden allocation bias by incorrectly treating chemically heterogeneous "no-scaffold" molecules as a single unit, which distorts generalization metrics across common benchmarks, and proposes an "Empty-Scaffold-Aware" repair to restore balanced representation and accurate performance assessment.

Tao Song, Yong Wang, Shuang Wang, Xun Wang2026-07-13

💻 computer science

C3Q-MARL: A Framework for UAV SwarmConnectivity and Collision Avoidance

This paper introduces C3Q-MARL, a connectivity-aware framework that integrates graph-theoretic topology control with a QAOA-inspired optimization module into multi-agent reinforcement learning to enhance UAV swarm coordination, collision avoidance, and connectivity preservation under partial observability and communication constraints.

Mazyar Taghavi, Javad Vahidi2026-07-10

💻 computer science

Scale-Dependent Performance of YOLOv12 andYOLOv11 for Automated Blood Cell Detection: A Controlled Benchmark on BCCD

This study presents the first scale-by-scale benchmark of YOLOv11 and YOLOv12 variants on the BCCD dataset, revealing that while their overall mean performance is nearly identical, YOLOv12 excels at the nano scale for latency-critical applications whereas YOLOv11 outperforms it at medium and large scales, indicating that model selection should be driven by specific scale and recall requirements rather than a uniform assumption of superiority.

Wenxi Tang, Yu Miao, Xiafang Chen2026-07-10

💻 computer science

RLHOARNet: A MONAI-Based 3D U-Net withLightweight Residual Boundary Refinement forMulti-Modal Brain Tumor Segmentation

This paper introduces RLHOARNet, a MONAI-based 3D U-Net architecture featuring a lightweight residual boundary refinement module that achieves state-of-the-art performance and real-time inference speeds for multi-modal brain tumor segmentation on the BraTS 2020 dataset.

A Divyashree, Rajesh Sharma R, Akey Sungheetha2026-07-10

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