cs papers | Gist.Science

Causal Retrieval-Augmented Generation: ModifyingFake Correlations in AI-Driven Knowledge Systems through Algorithmic Nudging

This paper introduces Causal Retrieval-Augmented Generation (CR-RAG), a framework that models the RAG pipeline as a Structural Causal Model to mitigate spurious correlations and reduce hallucinations through backdoor adjustment, inverse-propensity reweighting, and counterfactual data augmentation, achieving significant performance gains on knowledge-intensive benchmarks, particularly for long-tail questions.

A.Jethose Vijayakumar, Rajendran Thavasimuthu, Ramkumar Sivasakthivel, Manikandan Rajagopal2026-07-27

📄 other

Diffusion Model-Based Image Restoration: Interactive Learning of Determinism and Stochasticity

This paper proposes a novel diffusion framework for image restoration that employs interactive modeling of determinism and stochasticity to effectively adapt to the heterogeneous requirements of diverse degradation tasks, achieving superior performance and interpretability across multiple restoration scenarios.

Sha Luo, Siyuan Peng, Dawei Zhao, Qingwei Gao2026-07-27

💻 computer science

Topology-Preserving Anisotropic Adaptive Yarn-Level Cloth Simulation Using Direction-Aware Energy Evaluation

This paper proposes a topology-preserving, direction-aware adaptive framework for yarn-level cloth simulation that dynamically adjusts constraint computation intensity based on local deformation and contact activity while employing visual upsampling to maintain high-fidelity woven structures without incurring prohibitive computational costs.

Jong-Hyun Kim2026-07-27

📄 other

IBKA-Transformer: An Improved Black Kite Algorithm Optimized Transformer for Industrial Robot Bearing Fault Diagnosis

This paper proposes IBKA-Transformer, a novel fault diagnosis method that integrates an improved Black Kite Algorithm with a Transformer model to optimize hyperparameters and select features, achieving 99.86% accuracy in industrial robot bearing fault diagnosis.

Jiangnan Su, Jun Huang2026-07-27

📄 other

Dual-Critic Uncertainty-Gated Reinforcement Learning for Vision-Dropout-Robust Image-Based Visual Servoing

The paper proposes DCUG-PPO, a dual-critic reinforcement learning controller that anchors its policy to a model-based fallback via an uncertainty-gated mechanism, achieving significantly higher reliability and smoother control than single-critic PPO and classical baselines in image-based visual servoing under camera dropout, while acknowledging limitations in hardware validation and broader algorithmic comparisons.

Md Hasibuzzaman, Gene Eu Jan2026-07-27

📄 other

ESSIM: A Probabilistic Swarm Optimization Algorithm Based on Bayesian Statistical Inference and Uncertainty-Guided Search

This paper introduces ESSIM, a novel probabilistic swarm optimization algorithm that leverages Bayesian statistical inference and individual particle uncertainty to maintain swarm diversity and avoid local minima, thereby outperforming classical PSO on multimodal benchmarks and Gaussian Process Regression hyperparameter optimization tasks despite requiring longer computation times.

Hacene Benkhoula, Kamel Eddine Hemsas, Saad Mekhilef2026-07-27✓ Author reviewed ⓘ

📄 other

Robust Video Steganography Against Recompression and Arbitrary Cropping via Dual-Layer PN Synchronization

This paper proposes a robust video steganography method that combines MEC-AQIM embedding in the DWT-SVD domain with a dual-layer pseudo-noise synchronization mechanism to effectively recover secret data from videos subjected to both recompression and arbitrary cropping.

Yanzhe Zhang, Yingnan Zhang, Ling Wen, Hemin Yin, Min Shi2026-07-27

📄 other

A bio-inspired hybrid lifelong learning based on self-selective memristors

This paper proposes a bio-inspired hybrid lifelong learning system that co-designs a Drosophila-human hybrid algorithm with self-selective memristor hardware to overcome catastrophic forgetting and energy inefficiencies, achieving significant speed and energy improvements over traditional CMOS accelerators.

Yishu Zhang, Xuemeng Fan, Guobin Zhang, Zhejia Zhang, Xinheng Mei, Zijian Wang, Wenjue Zhou, Daying Sun, Lei Deng, Mingk (…)2026-07-27

📄 other

Leakage-Controlled Machine Learning for European Cd, Hg, and Pb Emission Inventories

This paper presents an auditable, leakage-controlled machine learning framework that harmonizes heterogeneous European emission data to accurately predict short-term spatial updates for cadmium, mercury, and lead inventories, achieving significant error reductions over baselines while explicitly defining operational limits for anomaly screening and expert prioritization rather than unrestricted forecasting.

Tianyi Guan, Jennifer Uyen-Vi Nguyen2026-07-27

📄 other

A Biomedical Benchmark and Modular RAG Framework for Text2Cypher

This paper introduces bio2C, a FAIR-compliant benchmark of 2,500 curated natural language-Cypher pairs, and a modular Retrieval-Augmented Generation framework that significantly improves Text2Cypher accuracy for biomedical knowledge graphs by leveraging retrieved examples over schema-based prompting.

Emanuele Cavalleri, Nada Bou Kanaan, Marco Mesiti2026-07-27

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