💻 Category

cs

2579 papers

💻 computer science

Multi-Objective Incremental Path Planning with Learning-Guided Sampling and Kinematic Constraints for Autonomous Vehicles in Dynamic Occupancy Grid Environments

This paper proposes LKSD-PRRT*, a modular path planning framework for autonomous vehicles in dynamic grid environments that integrates learning-guided sampling, multi-objective incremental rewiring, three-stage smoothing, and dynamic path repair to significantly enhance planning success, path quality, and recovery efficiency compared to existing methods.

Yuhui Du, Xueguang Liu, Pengyu Bu, Jiapeng Li2026-09-23
💻 computer science

SPT-CCRNet: Explainable Multi-Structure Segmentation of RenalBiopsy Pathology Images via Structured Progressive Tokenizationand Interventional Context Reasoning

The paper introduces SPT-CCRNet, an explainable deep learning framework that combines structured progressive tokenization, graph reasoning, and interventional context attribution to achieve state-of-the-art multi-structure segmentation of renal biopsy images, significantly outperforming existing baselines while demonstrating the importance of its specific architectural components.

Tingting Guo, Xun Tang, Junjie Bai, Pinghua Li, Qi Ye, Zirui Chen, Jianmin Yin, Yuliang Zhang, Jun Zhang2026-09-23
💻 computer science

A Dual Layer Gated Multimodal Healthcare and Rehabilitation Recommendation Method

This paper proposes a dual-layer gated multimodal learning framework that dynamically integrates textual, numerical, and categorical medical data through hierarchical gating and adaptive loss mechanisms to improve the accuracy, interpretability, and generalization of healthcare and rehabilitation recommendations for an aging population.

Yuanyuan Wu, Yizhuo Guo, Zikai Feng, Mengxing Huang2026-09-23
💻 computer science

Analysis of Federated Aggregation under Model Poisoning and Backdoor Attacks: A Reconstructed Cross-Dataset and Cross-Architecture Benchmark

This paper presents a reconstructed cross-dataset and cross-architecture benchmark evaluating federated aggregation methods under various attacks, highlighting Trimmed Mean's superior clean performance and Krum's robustness against specific threats while critically identifying metric implementation flaws and provenance limitations that restrict the findings to descriptive comparisons rather than universal statistical claims.

Soumya Mazumdar, Vineet Kumar Rakesh, Tapas Samanta2026-09-23
💻 computer science

WaveInvNet: A Wavelet-Separated Dynamic Involution Network for Multimodal Skin Lesion Classification

This paper proposes WaveInvNet, a lightweight multimodal deep learning architecture that integrates dermoscopic images with patient metadata using a novel Wavelet-Separated Dynamic Involution block to adaptively capture heterogeneous lesion features, achieving state-of-the-art performance in skin lesion classification on the HAM10000 dataset.

Mohamed Amine Ibrahimi, Abdelghafour Abbad, Rachid Ben Abbou, Khalid Abbad2026-09-23
💻 computer science

News Headline Classification for Electronics Supply-Chain Disruption Detection via Data-Anchored Label Attention

This paper introduces Data-Anchored Label Attention (DALA), a parameter-efficient method that enhances electronics supply-chain disruption detection by enriching label queries with expert definitions and discriminative anchors, achieving a significant improvement in macro F1 scores over baseline models on a dataset of expert-verified headlines.

Mohamed ElDeeb, Fahima Maghraby, Menna Kamel2026-09-23
💻 computer science

ICD2Bert: ICD Bert Encodings for Clinical Outcome Prediction on Routine Health Insurance Data

This paper introduces ICD2BERT, a standard BERT model pretrained on ICD codes without domain-specific modifications, and demonstrates through extensive benchmarking that such architectural complexities often fail to outperform simpler baselines, highlighting that data quality, scale, and pretraining are more critical for clinical outcome prediction than model sophistication.

Jonas Harriehausen, Miriam Cindy Maurer, Jacqueline Michelle Metsch, Zully Ritter, Lisa Weller, Thorsten Pollmann, Matth (…)2026-09-23
💻 computer science

Bayesian Concept Consolidation for Concept-Level Stability in Continual Learning

This paper proposes Bayesian Concept Consolidation (BCC), a continual learning framework that utilizes a concept-stability loss and uncertainty-aware mechanisms to preserve the semantic integrity of learned concepts, demonstrating through the new Knowledge Stability Index (KSI) that standard accuracy-preserving methods fail to prevent concept-level drift.

Simachew Alamneh, mohammed Abebe, Chernet Erdachew2026-09-23
💻 computer science

From Factors to Argument Networks: Issue-Level Legal Representation and Alignment with Written Judicial Reasons in Employment-Relationship Determination

This paper proposes an issue-level legal representation framework using argument networks to capture nuanced factual states, legal rules, and judicial reasoning in employment-relationship cases, demonstrating that such granular representations significantly outperform traditional binary methods in predicting outcomes and identifying the specific grounds for judicial decisions.

YANG YANG, CAIXIA xie2026-09-23