A highly customizable agentic harness for arXiv-ready ML/AI review papers (and beyond). It drives agentic AI like Codex CLI and Claude Code through a gated LaTeX workflow with verified BibTeX citations.

Mamba in Vision: A Comprehensive Survey of Techniques and Applications

Competition for best expository article on cutting-edge ML research

This is a complete information on a small review paper I have worked on. It is based on Machine Learning. The topic is Effects of News Sentiment on Financial Market trends

LLM-powered tool to draft a narrative review paper on any topic of your choice.

This paper investigates the ”double field theory” (DFT) and the connection to the double copy method that shows that gauge & gravity theories are remarkably similar at the quantum level.

A research paper written for, and presented in, the "Verification, Validation and Maintainance of Software Systems" course of the Athens University of Economics and Business.

This repository is dedicated to the Call for Papers (CFP) initiative, inviting researchers and scholars to submit their academic work for UIJRT (United International Journal for Research & Technology). The project provides comprehensive guidelines, important deadlines, and insights into the submission and peer review process.

Three different papers on same topic with three different approaches to solve have been studied and compared like a review paper on the topic "Fake Image Detection" of image processing and computer vision.

Comprehensive review of epilepsy in children with cerebral palsy, covering pathophysiology, neuroimaging, EEG, genetics, diagnosis, treatment, rehabilitation, artificial intelligence, machine learning, and future research directions.

This paper discusses about the progress AI has made in the healthcare domain and what the future of AI looks like. It also discusses about the implementation opportunities various AI technologies provide in various fields of healthcare & clinical workflow, how AI systems will boost healthcare to restore human touch in patient-physician encounters.