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 · 141–150 / 438

Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction

The paper introduces Chem-GMNet, a novel sphere-native geometric transformer that replaces standard transformer modules with spherical counterparts to achieve state-of-the-art molecular property prediction performance on MoleculeNet benchmarks, often outperforming large-scale pretrained SMILES-based models with significantly fewer parameters and no pretraining.

Deepak Warrier, Raja Sekhar Pappala2026-05-14✓ Author reviewed 🧬 q-bio

VERA-MH: Validation of Ethical and Responsible AI in Mental Health

The paper introduces VERA-MH, a clinically validated framework that evaluates the safety of AI chatbots in mental health contexts—specifically regarding suicidal ideation—by simulating diverse user interactions with role-playing agents and assessing responses using a structured, clinical rubric.

Luca Belli, Kate H. Bentley, Josh Gieringer, Emily Van Ark, Nilu Zhao, Pradip Thachile, Matt Hawrilenko, Millard Brown, Adam M. Chekroud2026-05-14✓ Author reviewed 🤖 cs.AI

Diversity in Evolutionary Status and Magnetic Activity among Solar-Type Twin Detached Eclipsing Binaries

This study presents a combined photometric and spectroscopic analysis of four solar-type twin detached eclipsing binaries, revealing significant diversity in their evolutionary stages and magnetic activity levels despite their nearly equal masses, while also identifying a potential tertiary companion in one system.

Fang-Bin Meng, Li-Ying Zhu, Sheng-Bang Qian, Lin-Jia Li, David Mkrtichian, Nian-Ping Liu, Ahmet Dervişoğlu, Er-Gang Zhao, Boonrucksar Soonthornthum, Sergey Zvyagintsev, Somsawat Rattanasoon, Jia Zhang2026-05-14✓ Author reviewed 🔭 astro-ph

Neurodata Without Boredom: Benchmarking Agentic AI for Data Reuse

This paper benchmarks agentic AI's ability to automate the reuse of fragmented neuroscience data by testing its performance on loading, understanding, and reformatting datasets from eight recent studies, revealing that while agents excel at individual sub-tasks, they currently struggle to produce fully error-free end-to-end solutions and require human-in-the-loop oversight.

Ling-Qi Zhang, Kristin Branson2026-05-14✓ Author reviewed 🤖 cs.LG