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.
949 papers reviewed by authors · 191–200 / 949
This paper investigates the tunneling-induced hybridization and coherent oscillations of Jackiw-Rebbi zero modes in a modified Su-Schrieffer-Heeger chain, demonstrating how finite overlap between bound states at Dirac-type gap closing points enables controllable topological quantum-state transfer.
OmniPilot is an uncertainty-aware inference advisor for heterogeneous GPU clusters that predicts serving costs and abstains from unreliable configurations using conformally calibrated quantile models and out-of-distribution detection, thereby optimizing economic utility with high accuracy across diverse hardware and precision settings.
This study demonstrates that while LLM personas can reveal some stable personality-driven patterns in visualization design tasks like color assignment and chart choice, their outputs are heavily dependent on model configuration and task context, positioning them as useful exploratory probes rather than reliable substitutes for human participants.
This study extends modified wavenumber analysis to Physics-Informed Neural Networks (PINNs) to systematically evaluate their spectral accuracy on high-frequency wave problems, revealing that deeper architectures, specific activation functions like sinusoidal or tanh-Gaussian, and an optimal number of Fourier modes () are critical for minimizing dispersion and dissipation errors.
This study presents a three-phase deep learning framework that combines LSTM-based pH prediction with Deep Reinforcement Learning control, validated against African soil profiles using synthetic data, to provide a scalable and transferable solution for optimizing mine reclamation in data-scarce Sub-Saharan regions.
This study presents an interpretable forecasting framework using penalized logistic regression and bootstrap stability selection on historical team data to predict FIFA World Cup progression, identifying key predictors like market value and FIFA ranking while forecasting Argentina, France, Spain, England, Germany, and the Netherlands as top contenders for the 2026 tournament.
This mixed-method study demonstrates that brand communication, when moderated by CSR and cultural lifestyles, serves as a strategic tool for building reputable brands, enhancing consumer preferences, and translating into brand equity.
This study demonstrates that depositing ZnO thin films via a spray pneumatic technique at 450°C yields optimal structural, optical, and electrical properties, including a maximum crystallite size of 15.19 nm, approximately 85% transparency, a band gap of 3.31 eV, and the lowest electrical resistivity of 0.064 Ω·cm.
This paper presents an ultra-compact, two-stage on-device audio cascade that utilizes a lightweight 2D CNN for snore detection and an adapted Coordinate Attention mechanism for classifying sleep apnea events, achieving high accuracy with a 93.2% parameter reduction compared to baselines.
Based on an analysis of 4.3 million human-AI conversations, this paper finds that AI primarily serves as a practical intermediary for routine political tasks rather than a public forum for expression, though major events like the 2024 U.S. election can temporarily shift user behavior toward more expressive and ideologically charged interactions.