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.
1367 papers reviewed by authors · 1331–1340 / 1367
This paper proposes two-stage sequential estimators for relative risk, odds ratio, and their logarithms that guarantee a target mean-square error for any population parameters while maintaining a controlled sample size ratio and achieving high efficiency near the Cramér-Rao bound.
This paper demonstrates that applying Deep Neural Networks to a 2x2 array of linearly-graded Silicon Photomultipliers significantly improves position resolution and linearity while increasing the number of resolvable pixels by a factor of 5.7 to 12.1 compared to traditional reconstruction methods.
This paper introduces the Kinematically Diagonalized Current Basis (KDCB), a generative framework that constructs dimension-8 SMEFT operators from conserved Noether currents to resolve kinematic mixing, ensure unique energy scaling in scattering amplitudes, and facilitate the application of positivity bounds and global fits for interpreting new physics.
This paper proposes a novel unsupervised framework for Invariant Risk Minimization that redefines invariance through feature distribution alignment, introducing the linear PICA and deep generative VIAE methods to learn robust, environment-invariant representations from unlabeled data.
This paper introduces a post-training paradigm that leverages knowledge graphs as implicit reward models to guide large language models in learning compositional reasoning from axiomatic facts, enabling a 14B model to outperform frontier systems on complex multi-hop medical queries through path-derived supervision.
This paper demonstrates that directional CDNV (decision-axis variance) is the key geometric quantity governing both strong few-shot transfer and low multitask interference in self-supervised learning, as its minimization during pretraining leads to tight generalization bounds and nearly orthogonal decision axes across tasks.
Contrary to the conventional expectation that electrowetting promotes droplet spreading, this study reveals that applying DC voltage to specific microtextured, lubricant-infused surfaces in a Cassie wetting state induces rapid tangential droplet ejection due to unbalanced electrocapillary forces and minimal pinning, offering a new paradigm for controlled droplet transport.
This paper presents a simultaneous analysis of measured and calculated data to predict the prompt fission neutron spectra (PFNS) of 233U(n,F) up to 20 MeV, establishing that while its spectrum is harder than 235U(n,F) but softer than 239Pu(n,F), the underlying pre-fission contributions and energy partitioning differ significantly due to fissility and competing reaction channels.
This study demonstrates that a Pechini sol-gel synthesis method with cationic molecular mixing can efficiently produce high-quality Li-doped Bi-2223 superconductors, achieving a maximum critical temperature of 111.4 K at 5 mol% Li doping while revealing unique layer-by-layer crystalline growth and flux creep mechanisms.
This paper reviews how recent advancements in Large Momentum Effective Theory (LaMET), including improved renormalization schemes, higher-order matching kernels, and novel lattice operators, are enhancing the precision and reliability of first-principles lattice QCD calculations for proton parton distributions.