cs papers | Gist.Science

Structured Clinical Documentation as Upstream Data Engineering: A Systematic Review of Ambient-AI and LLM-Driven Inputs for Predictive Modeling in Healthcare

This systematic review of 52 studies demonstrates that structured clinical documentation technologies, ranging from rule-based templates to ambient-AI and LLM-driven systems, act as critical upstream data engineering mechanisms that enhance data quality and significantly improve the predictive performance of machine learning models for key healthcare outcomes, though further research is needed to address gaps in external validation and bias mitigation.

Raaga Likhitha Musunuri, Dhruvi Mohansinh Parmar, Nitya Phani Santosh Oruganty2026-07-30

💻 computer science

FL-SNNIDS: Federated Spiking Neural Networks for Energy-Efficient Intrusion Detection in Agricultural SDN-IoT Networks

This paper proposes FL-SNNIDS, a federated Spiking Neural Network framework that enables energy-efficient, low-latency, and privacy-preserving intrusion detection for resource-constrained agricultural SDN-IoT networks by achieving high accuracy through collaborative model training without raw data exchange.

Selma Amrani, Chirihane Gherbi, Khedidja Medani, Hakim Mabed2026-07-30

💻 computer science

A Bibliometric Review of Emerging Trends and Strategic Mapping of Defense Mechanisms in Large Language Models from 2024 to 2026

This bibliometric review of 137 high-quality articles from 2024 to 2026 maps the rapidly evolving landscape of Large Language Model defense mechanisms, identifying key thematic shifts toward vulnerability detection and benchmarking while highlighting critical gaps in evaluation infrastructure that pose governance risks for high-stakes deployments.

Sebastián Vargas-Yáñez, Sergio Tobón2026-07-30

💻 computer science

Multi-View Camera Perception System for Variant-Aware Automated Vehicle Inspection and Defect Detection

This paper presents Automated Vehicle Inspection (AVI), a multi-view deep learning system that integrates synchronized 360-degree imaging with specialized detection models and a rule-based engine to achieve high-accuracy, variant-aware vehicle verification and defect detection at a throughput of 3.3 vehicles per minute.

Yash Kulkarni, Raman Jha, Renu Kachhoria2026-07-30

💻 computer science

Computational Personality Assessment: A Data- Driven Machine Learning Approach Using Engineered Behavioral Features

This paper presents a data-driven machine learning pipeline that significantly improves introvert-extrovert classification accuracy to 91.90% by engineering three composite behavioral features and evaluating 13 algorithms, demonstrating that K-Nearest Neighbors performs best within a statistically robust framework.

MEERA SOLGAMA, ZEELKUMAR BHAVSAR2026-07-30

💻 computer science

Automatic Discovery of Intra-Class Sub-Structure for Supervised Tabular Classification: Offline Clustering vs. Joint Sub-Center Training

This rigorous empirical study demonstrates that while conventional offline clustering of penultimate features to discover intra-class sub-structure is unreliable and often degrades tabular classification performance, a joint end-to-end sub-center training approach effectively mitigates these risks, though the authors conclude that no robust heuristic currently exists to predict when such sub-structure discovery is beneficial.

Seyed Ali Zaribaf, Mohammad Roustaei2026-07-30

💻 computer science

An automated pipeline for biomedical research hotspot mining integrating contextual embeddings and temporal citation ranking: a case study in cataract research

This paper presents a fully automated pipeline that integrates BioBERT contextual embeddings, hybrid clustering, and temporal citation ranking to effectively map biomedical research landscapes and identify evolving hotspots, as demonstrated through a comprehensive case study on cataract research.

Xiaoming Wu, Keqiang Wang, Xiujing Shi, Yuan Ni, Guoxin Wang, Dongle Liu, Jiajun Sun, Zhen Guo2026-07-30

💻 computer science

Global Interaction Modeling with Human Knowledge for Important Traffic Objects Identification

This paper proposes a novel framework for identifying important traffic objects that leverages Bird's-Eye View global interaction modeling and a Contrastive Language-Motion Pre-training approach to integrate human knowledge, thereby overcoming the limitations of existing 2D visual methods in spatio-temporal reasoning and dynamic understanding.

Yiming Huang, Faliang Chang, Chunsheng Liu, Penghui Hao, Jun Zhou2026-07-30

💻 computer science

CATD-LPT-CFPM- Cluster Aware Top-Down Linear Prefix Tree for Closed Frequent Pattern Mining

The paper proposes the CATD-LPT-CFPM framework, which enhances closed frequent pattern mining by clustering transactions to reduce search space and employing a multi-level pruning strategy with a Top-Down Closedness Pruning mechanism to minimize redundant processing and memory usage, despite incurring some overhead from clustering and tree construction.

M Sinthuja, P Saranya, M. Diviya2026-07-30

💻 computer science

Canonical Alignment and Weighted Neural Network for Autonomous Part Defect Identification in 3D Point Clouds

This paper proposes an enhanced PointNet-based framework for autonomous defect identification in 3D point clouds that utilizes deterministic SVD-based canonical alignment and weighted cross-entropy loss to overcome geometric variability and class imbalance, achieving improved accuracy and reduced inference latency for real-time industrial inspection.

Qingze Zou, ElHussein Shata, Baihui Chen, Yuebin Guo2026-07-30

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