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.
438 papers reviewed by authors · 171–180 / 438
This paper proposes an adaptive execution framework for World Action Models that employs a lightweight Future Forward Dynamics Causal Attention verifier to dynamically adjust action chunk sizes based on prediction-reality consistency, thereby significantly improving both the efficiency and success rate of robotic manipulation tasks.
This paper argues that when economic reforms face status-quo inertia in coordination games, interventions that alter the feasible action space—such as deleting or replacing options—are more effective at shifting equilibria than marginal price-based incentives, because they fundamentally change the strategic structure rather than merely adjusting payoffs within an entrenched system.
This paper introduces the Bayes factor-Bayes factor (BB) plot, a diagnostic tool that leverages the relationship between Bayes factors and their distributions under competing hypotheses to validate calculation accuracy and efficiently estimate background distributions, as demonstrated through applications in gravitational wave astronomy including the statistical significance assessment of GW231123.
This paper mathematically establishes scaling laws and exchange rates to quantify the value of brain data in improving machine learning models, identifying specific conditions regarding task-brain alignment, noise, and sample sizes where collecting neural recordings is beneficial for performance and robustness.
The paper introduces FairHealth, an open-source Python library designed to bridge critical gaps in healthcare AI for low-resource settings by providing a unified, modular framework that integrates fairness auditing, privacy-preserving federated learning, low-bandwidth explainability, and specialized tools for Global South datasets.
This paper proposes a non-analytic model demonstrating that the Boson peak in amorphous solids originates solely from fluctuations in coordination numbers, while fluctuations in spring strength primarily contribute only to damping.
This paper introduces a family of fault-tolerant non-CSS quantum error-correcting codes generated via graph states and the bare-ancilla method, demonstrating their resilience against hook errors and superior performance compared to existing flag-qubit and bare-ancilla approaches under various noise models.
This study compares Hi 21-cm emission-absorption observations from the GWA and LAB surveys with TIGRESS numerical simulations to determine that the neutral interstellar medium consists of approximately 19.8% cold, 32.5% unstable, and 47.8% warm phases, a distribution that aligns with simulation results and highlights the need for future sensitive radio observations to further constrain these gas fractions.
This paper introduces Wasserstein Lagrangian Mechanics (WLM), a novel framework and algorithm that learns second-order population dynamics from temporal snapshots by minimizing a damped action, thereby overcoming the limitations of gradient flows to accurately model complex behaviors like periodicity, vortex dynamics, and flocking.
This paper presents a uniformly selected sample of 930 intermediate-mass black hole active galactic nuclei from SDSS DR17, extending the redshift coverage of low-mass AGNs to and revealing a potential cosmic evolution in accretion activity characterized by declining maximum accretion rates and luminosities at lower redshifts.