cs papers | Gist.Science

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

📄 other

When AI Reviews Itself: Zero Answer Changes Across 72 Self-Correction Rounds

This study demonstrates that frontier large language models exhibit "performative self-correction" by generating extensive critical discourse without ever substantively revising their initial answers across 72 iterative review rounds, thereby challenging the efficacy of prompting-based correction strategies for improving AI reliability.

Abbas Hamidavi2026-07-27

📄 other

Retrieval-Assisted Instantiation of Natural-Language Optimization Problems

This paper presents a transparent, retrieval-assisted framework that grounds natural-language numeric evidence into structured optimization schemas, demonstrating that while schema retrieval is highly effective, the primary bottleneck for automating optimization problem instantiation lies in the downstream task of accurately matching extracted numbers to their corresponding slots.

Soroush Vahidi2026-07-27

📄 other

BoneNet: A Multimodal Deep Learning Framework with Dual-Modality Explainability for Automated Peri-Implant Bone Loss Detection and Severity Grading

This study introduces BoneNet, a multimodal deep learning framework that integrates a YOLOv8m backbone with dilated residual attention blocks and tabular data fusion to achieve high-accuracy automated detection, severity grading, and explainable depth estimation of peri-implant bone loss while transparently identifying performance limitations in severe cases.

Muralidhar Billa, Merin Thomas, Vidya M J2026-07-27

📄 other

Implementation and evaluation of space-efficient traversal algorithms on succinct de Bruijn graphs

This paper presents the first implementation and evaluation of space-efficient BFS and DFS traversal algorithms on succinct de Bruijn graphs, demonstrating significant reductions in auxiliary memory usage (up to 11×) and overall memory footprint (up to 2.36×) on a graph with 800 million edges.

Fikrat Talibli2026-07-27

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