cs papers | Gist.Science

A Spectrogram-Based Deep Learning Framework for Automatic Swara and Gamaka Recognition in Carnatic Veena Performances

This paper proposes a spectrogram-based deep learning framework utilizing Short-Time Fourier Transform and Mel spectrograms with convolutional neural networks to automatically recognize swaras and gamakas in Carnatic Veena performances, addressing unique acoustic challenges and establishing a foundation for applications in transcription, education, and digital archiving.

SUDHI S2026-07-17

💻 computer science

Human-in-the-loop GenAI advising for community college pathway decision-making: a design-based case study of requirement-group modeling and privacy-preserving student-support design

This design-based case study addresses the gap in GenAI research regarding community college advising by proposing a privacy-preserving framework and eight design principles that position AI as an explanatory layer for pathway planning while maintaining human oversight, protecting student data, and fostering learner agency.

Emery Peck2026-07-17

💻 computer science

Zero-shot Generalizable LiDAR Semantic Segmentation via Scene-Sensor Disentanglement

This paper introduces LiSeer, a zero-shot generalizable LiDAR semantic segmentation framework that achieves robust cross-sensor performance by disentangling scene-intrinsic geometry from sensor-specific sampling effects through a diffusion-based scene reconstruction and controllable sampling pipeline.

Shaobing Xu, Zikun Xu, Shuocheng Yang, Jiahao Wang, Keqiang Li, Jianqiang Wang2026-07-17

💻 computer science

Goal-Aware Adaptive Regulation Across Modalities: Evolutionary Architecture Search for Transformer Language Models on a Consumer AMD GPU

This paper demonstrates that the GaaR evolutionary architecture search framework, originally validated on convolutional networks, successfully transfers to autoregressive transformer language models on a consumer AMD GPU via DirectML, achieving competitive performance and revealing that regulated exploitation outperforms random search on structured landscapes while favoring wide-shallow architectures under fixed step budgets.

Leon Sandler2026-07-17

💻 computer science

A Distributed CatBoost Approach with Weighted Aggregation for STI/HIV Risk Prediction

This paper proposes a privacy-preserving, distributed CatBoost framework with weighted aggregation that achieves high accuracy in predicting STI and HIV risks across eight countries without requiring centralized data, thereby offering a robust alternative to traditional centralized machine learning models.

Zhaohui Tang, Yan Li, Abdulkadir Sengur, U. Rajendra Acharya2026-07-17

💻 computer science

NAE-VC: Neural Arithmetic Encoding as a Learned Replacement for CABAC in Modern Video Codecs

NAE-VC is a modular, learned entropy coding framework that replaces the standard CABAC engine in H.264, H.265, and H.266 codecs with a neural architecture combining context aggregation, Gaussian mixture modeling, and hyperpriors to achieve significant bitrate savings while maintaining full compatibility with existing video coding standards.

Reka Sandaruwan Gallena Watthage, Anil Fernando2026-07-17

💻 computer science

MUNNA: A Multi-strategy, Uncertainty-driven, Nested Neuro-ensemble Algorithm for Disease Diagnosis with Closed-loop Explainability Feedback

This paper introduces MUNNA, a novel three-stage hybrid framework that integrates a GWO-SA metaheuristic for feature selection, an uncertainty-weighted stacking ensemble, and a closed-loop SHAP feedback mechanism to achieve state-of-the-art disease diagnosis performance on the Breast Cancer Wisconsin dataset while addressing limitations in local optima stagnation and static ensemble weighting.

Md. Maruf Sharker Munna2026-07-17

💻 computer science

DAÏO: A High-Specificity Real-TimeVision-Based Fall Detection SystemUsing Advanced Kinematic Tracking andComputer Vision

The paper presents DAÏO, a novel edge-capable vision-based fall detection system that combines a lightweight pose estimator, an adaptive Extended Kalman Filter, and a Triple-Check Logic Engine to achieve high specificity (96.4%) and significantly reduce false positives from daily activities and religious prostrations while maintaining real-time performance on consumer hardware.

Alamin Abubakar Nataala2026-07-17

💻 computer science

STAC-MV: Spatio-Temporal Adaptive Context for Neural Multiview Video Compression

STAC-MV is the first transformer-based neural multiview video compression framework that leverages geometry-aware adaptive context selection and cross-view attention to achieve significant BD-rate improvements over conventional standards across diverse camera configurations while substantially reducing encoding time.

Reka Sandaruwan Gallena Watthage, Anil Fernando2026-07-17

💻 computer science

Multi-Stage Alignment of Large Language Models for Popularity Bias Mitigation in Generative Movie Recommendation

This paper proposes a multi-stage alignment pipeline combining preference extraction, supervised fine-tuning, and Direct Preference Optimization to effectively mitigate popularity bias in LLM-based movie recommenders, achieving improved novelty and catalog coverage while maintaining competitive accuracy.

Subham Raj, Krishnakant Chourey, Sriparna Saha, Brijraj Singh, Niranjan Pedanekar2026-07-17

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