pAI/MSc: ML Theory Research with Humans on the Loop

Fuente: arXiv
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Main Authors: Abdelmoneum, Mahmoud, Beneventano, Pierfrancesco, Poggio, Tomaso
Format: Preprint
Published: 2026
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author Abdelmoneum, Mahmoud
Beneventano, Pierfrancesco
Poggio, Tomaso
author_facet Abdelmoneum, Mahmoud
Beneventano, Pierfrancesco
Poggio, Tomaso
contents We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific ideation, nor fully automated research. It is narrower and more practical: to reduce by orders of magnitude the human steering required to turn a specified hypothesis into a literature-grounded, mathematically established, experimentally supported, submission-oriented manuscript draft. pAI/MSc is built with a current emphasis on machine learning theory and adjacent quantitative fields.
format Preprint
id arxiv_https___arxiv_org_abs_2604_20622
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle pAI/MSc: ML Theory Research with Humans on the Loop
Abdelmoneum, Mahmoud
Beneventano, Pierfrancesco
Poggio, Tomaso
Artificial Intelligence
Machine Learning
Multiagent Systems
We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific ideation, nor fully automated research. It is narrower and more practical: to reduce by orders of magnitude the human steering required to turn a specified hypothesis into a literature-grounded, mathematically established, experimentally supported, submission-oriented manuscript draft. pAI/MSc is built with a current emphasis on machine learning theory and adjacent quantitative fields.
title pAI/MSc: ML Theory Research with Humans on the Loop
topic Artificial Intelligence
Machine Learning
Multiagent Systems
url https://arxiv.org/abs/2604.20622