Papers where the original authors have engaged with our plain-language explanation.
For every paper on this page, at least one of the original authors has seen our plain-language explanation and engaged with it — either confirming it reads accurately or requesting corrections that we then applied. An endorsement does not mean the authors formally approve every sentence, but it does mean the explanation has passed the eyes of the people who wrote the paper.
948 papers reviewed by authors · 131–140 / 948
This paper analyzes the stability of continuous generative flow models parameterized by Graph Neural Networks, deriving explicit bounds on how structural perturbations affect generated signals and proposing a regularized training strategy that enhances robustness to graph noise without compromising output quality.
This paper introduces FMMVCC, a Mamba-based deep clustering framework that combines state space sequence modeling with multi-view self-supervised learning to efficiently capture long-range temporal dependencies in univariate time series, achieving state-of-the-art performance across 15 benchmark datasets without requiring manual labels.
By utilizing long gamma-ray bursts as unbiased tracers of star formation at high redshifts, this study derives a cosmic star formation rate density that naturally explains cosmic reionization without extreme assumptions and reveals a significant population of faint galaxies evolving from magnitudes of -14 to -15 at z~6 down to -10 to -11 at z~10.
This paper addresses the limitations of existing tools in assessing operating system vulnerabilities within Software-Defined Vehicles (SDVs) by presenting and releasing a comprehensive, Docker-based solution that combines systematic CVE analysis with exploitability evaluation to enhance the security and resilience of next-generation automotive systems.
This study presents an Arduino-based analog classroom system that effectively simulates and teaches the automation mechanisms of water table management in drainage engineering through real-time sensor data, automated control, and visual data logging.
This study presents three high-resolution cryo-EM structures of the human SET8 catalytic domain bound to nucleosomes, revealing how specific arginine-mediated anchoring to the acidic patch and dynamic conformational transitions facilitate the recognition and monomethylation of histone H4 lysine 20.
This study demonstrates that *Acidithiobacillus thiooxidans*-mediated bioleaching effectively removes alkali and alkaline earth metals from agricultural biomass residues under optimized conditions, significantly reducing ash-related combustion issues and enhancing energy properties to enable sustainable thermochemical conversion within a circular bioeconomy.
This study introduces a novel MACB-ResNet deep learning model that significantly improves the accuracy of classifying virtual taste stimuli from facial surface electromyography (sEMG) signals to 86.32%, outperforming traditional and standard deep learning classifiers for applications in digital health and food technology.
This paper presents coordinated multiwavelength observations of SS 433 using XRISM, optical, and near-infrared telescopes in 2024 and 2025, revealing high-resolution X-ray spectral details of jet velocity modulations, a potential optical lag behind X-rays, and distinct optical flaring behavior that contrasts with the stable X-ray and near-infrared emission.
Using the OASIS-3 dataset and advanced cerebral imaging, this study reveals that while dementia is associated with decreased structural connectivity in the hippocampus and temporal lobe, it surprisingly leads to increased connectivity in the precuneus, cuneus, and insula.