✓ Reviewed

Author-Reviewed Papers

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.

950 papers reviewed by authors · 451–460 / 950

📄 genetic and genomic medicine

DHDDS-related juvenile parkinsonism is caused by impaired lipid metabolism, glycosylation, and mitochondrial dysfunction, which can be rescued by NAD⁺ treatment.

This study demonstrates that DHDDS-related juvenile parkinsonism arises from impaired lipid metabolism, glycosylation defects, and mitochondrial dysfunction in patient-derived brain organoids, and that these pathological features, along with associated clinical symptoms, can be effectively rescued by NAD⁺ precursor (NMN) treatment.

Muffels, I. J. J., Kantautas, K. A., MacDonald, G., Garapati, K., Pasupuleti, R. R., Tinker, R. J., Shah, R., Thevandava (…)2026-06-05✓ Author reviewed ⓘ
⚛️ high-energy theory

Path integral quantization of tensionless bosonic strings with Carroll-Weyl ghosts

This paper revisits the path integral quantization of tensionless bosonic strings by demonstrating that treating Carroll-Weyl scaling as a genuine local gauge symmetry necessitates extending the standard BMS $bc$ ghost system to a $bcs$ system, thereby fundamentally altering the BRST complex and the conditions for anomaly cancellation.

Sarthak Duary, Sourav Maji2026-06-04✓ Author reviewed ⓘ
⚛️ general relativity

First Constraints on the Ellipticities of Self-Interacting Fermionic Dark Matter Admixed Neutron Stars from Continuous Gravitational-Wave Searches

This paper presents the first constraints on the ellipticities and self-interaction parameters of fermionic dark matter-admixed neutron stars by analyzing LIGO O3 continuous gravitational-wave data, demonstrating that such searches can effectively probe "dark mountains" and exclude specific regions of dark matter parameter space.

Premachand Mahapatra, Andrew L. Miller, Prasanta Kumar Das2026-06-04✓ Author reviewed ⓘ
💬 NLP

Clinical Assistant for Remote Engagement Link (CARE-link): A Web-Based Electronic Health Records Software for Managing Diabetes

CARE-link is an open-source, web-based platform that leverages large language models to bridge clinicians and patients for improved gestational diabetes management by aggregating remote patient data, providing context-aware clinical decision support, and delivering personalized lifestyle guidance via WhatsApp.

Prince Ebenezer Adjei, Joshua Teye Tettey, Toufiq Musah, Audrey Agbeve, John Amuasi2026-06-04✓ Author reviewed ⓘ
💻 computer science

Think Fast and Far: Long-Horizon Online POMDP Planning via Rapid State Sampling

This paper introduces ROP-RAS3, a novel approximate online POMDP solver that leverages rapid state space sampling to generate diverse macro-actions, enabling efficient long-horizon planning in high-dimensional continuous and hybrid environments where it significantly outperforms state-of-the-art methods in success rate.

Yuanchu Liang, Edward Kim, J. Arden Knoll, Wil Thomason, Zachary Kingston, Lydia E. Kavraki, Hanna Kurniawati2026-06-04✓ Author reviewed ⓘ
💻 computer science

SoK: Post-Quantum Cryptography (PQC) Implementation in Software Systems

This Systematization of Knowledge (SoK) paper analyzes Post-Quantum Cryptography (PQC) implementation challenges through the Human, Organisation, and Technology (HOT) framework, revealing a critical imbalance where human and organisational factors are underexplored, and proposes the PQC-HOT model to guide a coordinated socio-technological transformation for successful integration.

R. D. N. Shakya, C. P. Wijesiriwardana, S. M. Vidanagamachchi, Nalin A. G. Arachchilage2026-06-04✓ Author reviewed ⓘ
💬 NLP

Learning Self-Interpretation from Interpretability Artifacts: Training Lightweight Adapters on Vector-Label Pairs

This paper demonstrates that training lightweight, frozen adapters on interpretability artifacts enables large language models to generate reliable, high-quality self-interpretations across tasks and scales without modifying the underlying model.

Keenan Pepper, Alex McKenzie, Florin Pop, Stijn Servaes, Martin Leitgab, Mike Vaiana, Judd Rosenblatt, Michael S. A. Gra (…)2026-06-03✓ Author reviewed ⓘ
📊 statistics

Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks

This paper provides a rigorous probabilistic analysis of deep Leaky ReLU networks to derive a Lyapunov exponent governing activation stability, revealing limitations in standard initialization methods and proposing a novel "Lyapunov initialization" that sets this exponent to zero to ensure optimal training stability.

Constantin Kogler, Tassilo Schwarz, Samuel Kittle2026-06-03✓ Author reviewed ⓘ