✓ 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.

948 papers reviewed by authors · 21–30 / 948

💬 NLP

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI

This paper introduces HALO (Hallucination-Aware Layered Oversight), a six-layer assurance architecture that achieves "zero hallucination" not by eliminating the inherent limitations of large language models, but by enforcing a system-level framework of grounded generation, constrained execution, multi-signal verification, calibrated abstention, total traceability, and continuous oversight to contain hallucinations as a manageable failure mode.

Bogdan Raduta, Horia Velicu, Alexandru Preda, Serban Chiricescu2026-07-21✓ Author reviewed ⓘ
⚡ electrical engineering

Luminosity-Adaptive Contrast Enhancement Using CLAHE for Retinal Fundus Images with Quantitative Validation and Comparative Analysis

This study proposes and validates a two-stage image enhancement pipeline that combines HSV-based luminosity correction with CLAHE applied to the Value channel, demonstrating superior quantitative performance in contrast and structural fidelity over standard HE and AHE methods for retinal fundus images while maintaining clinical processing speeds.

K. Mithra, Prem Kumar Santhanam2026-07-21✓ Author reviewed ⓘ
🤖 AI

Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment

The paper introduces AnthroDial, a closed-loop framework that unifies role-conditioned dialogue generation, executable multi-dimensional evaluation, and cognitive-diagnostic preference alignment to significantly improve human-like chat performance across diverse personas and scenarios.

Wentao Liu, Siyu Song, Xi Chen, Youjia Li, Xiaokun Wang, Min Ji, Ji Wang2026-07-21✓ Author reviewed ⓘ
📄 social_science

Environmental Literacy Profile of Pre-Service Biology Teachers Through SSI-STEAM Integrated Learning

This study reveals that SSI-STEAM integrated learning effectively cultivates a very high overall environmental literacy profile among pre-service biology teachers, particularly in awareness and behavior, though it highlights SSI-based critical thinking as the most challenging dimension requiring further curricular strengthening.

Rahmatia Thahir, Hartono Bancong, Nurlina Nurlina, Agustan Syamsuddin, Eny Syatriana2026-07-21✓ Author reviewed ⓘ
📄 medicine

Cancer Immunotherapy Implementation in Crisis-Affected MENA Settings (Lebanon, Sudan, and Iraq): A Pilot Descriptive-Analytical Cross-Sectional Study of Barriers, Clinical Readiness, and Policy Priorities

This pilot descriptive-analytical study of 23 oncology professionals in Lebanon, Sudan, and Iraq reveals that cancer immunotherapy access is severely limited by high costs, political instability, and supply chain disruptions, while confirming the feasibility of the research instrument for a future, larger-scale investigation to guide urgent policy and multilateral interventions.

Gazy EBRAHIM2026-07-21✓ Author reviewed ⓘ
📄 medicine

Computational In Silico Screening of Himalayan Phytochemicals Against the Oncogenic Chaperone Protein (AGR2): Exploring Nepal's Biodiversity for Accessible Cancer Therapeutics

This study utilizes in silico virtual screening to identify 11-O-Galloyl bergenin and related Himalayan phytochemicals as novel, high-affinity inhibitors of the oncogenic chaperone AGR2, establishing a preliminary structure-activity relationship for future experimental validation.

Sambriddha Karki2026-07-21✓ Author reviewed ⓘ
🤖 AI

Spatiotemporal Facial Action Unit Detection using Twin Cycle Autoencoders for Driver Monitoring

This paper proposes the Twin Cycle Autoencoder (TCA), a novel spatiotemporal architecture that integrates spatial appearance disentanglement and temporal trajectory consistency to robustly detect Facial Action Units for driver monitoring under challenging in-cabin conditions, achieving state-of-the-art performance on benchmarks while maintaining real-time throughput on embedded hardware.

Sai Sidharth D2026-07-21✓ Author reviewed ⓘ
🤖 AI

Pediatric Bone Age Prediction Using Deep Learning

This paper presents a deep learning approach using EfficientNet models, particularly EfficientNetB4 enhanced with an Additive Attention mechanism, to accurately predict pediatric bone age from hand X-rays, offering a more effective and automated solution for diagnosing endocrine disorders compared to conventional methods.

Al Zadid Sultan Bin Habib, Md. Ekramul Islam, Md Asif Bin Syed, Md Younus Ahamed, Tanpia Tasnim2026-07-21✓ Author reviewed ⓘ