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.
1335 papers reviewed by authors · 151–160 / 1335
This paper introduces KIR, a typed intermediate representation that treats building information models as versioned programs to systematically detect and represent seven specific failure modes in autonomous agent-authored construction, demonstrating significant improvements in error diagnosis and code compactness compared to direct host API manipulation.
By applying a novel simulated annealing framework to single-cell RNA-seq data from four human cancers, this study identifies five conserved T cell exhaustion drivers and twenty novel candidate genes while revealing tissue-specific exhaustion signatures that challenge the universal role of previously reported markers like NR4A1.
This study proposes a novel interdisciplinary framework that reinterprets carbon dioxide not merely as a geochemical disturbance but as a beneficial driver for enhancing long-term nuclear waste isolation through CO₂-induced carbonate mineral precipitation that seals fractures in host rocks.
This study demonstrates that ambient noise seismic interferometry can effectively monitor slope instability by detecting a rapid, spatially expanding drop in seismic velocity following the September 2022 flash flood in central Italy, which correlates with pore-pressure propagation and offers a promising proxy for forecasting hydro-geological hazards.
By positing that modern astrophysicists are increasingly burdened by administrative publication tasks while AI lacks the capacity for original discovery, the paper argues that deploying AI as an agent of publication rather than discovery can liberate human researchers to focus on fundamental physics, ultimately driving positive growth in the field.
This paper identifies and validates a "derivative-fidelity failure mode" in physics-informed neural networks, demonstrating that models trained solely on function values can achieve visually accurate approximations while producing significantly erroneous second derivatives, particularly in high-curvature regions.
This paper demonstrates that light decoherence, modeled as multichannel scattering in a Fabry-Perot microcavity, significantly alters the system's linear response by eroding cavity photon modes and suppressing the formation and spectral signatures of molecular polaritons.
This paper introduces ShopEase, a multi-agent generative AI framework for enterprise customer support that leverages local LLaMA 3.2 and hybrid retrieval, demonstrating through evaluation on 2,632 queries that dense FAISS retrieval outperforms sparse and reranked hybrid approaches in accuracy while avoiding the latency penalties associated with cross-encoder reranking.
This paper demonstrates a monolithically integrated mirror–phaseshifter–emitter system in a GaAs waveguide that utilizes a nano-opto-electro-mechanical phase shifter to actively control the optical phase between a quantum dot and its mirror image, thereby enabling real-time modulation of the local density of optical states and the emitter's radiative decay rate for programmable quantum photonic networks.
The greedy approach returns the lexicographically maximal feasible set for planar disks when rho <= phi; in the independent-holes model, 1/sqrt(2) is the sharp threshold for area optimality. This golden guarantee holds for any finite inventory of planar disks, while in higher dimensions, the guarantee is limited to packing at most five rings.