# The Agentification of Scientific Research: A Physicist's Perspective

arXiv: https://arxiv.org/abs/2604.14718 · HTML: https://mlsanity.com/paper/2604.14718/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 31 references that are in the map.
- First posted on arXiv 16 Apr 2026.

## Builds on (most cited first, 14 of 14)

- [ChemCrow: Augmenting large-language models with chemistry tools](https://mlsanity.com/paper/2304.05376/) (2023)
- [Agent Laboratory: Using LLM Agents as Research Assistants](https://mlsanity.com/paper/2501.04227/) (2025)
- [Accelerating scientific discovery with Co-Scientist](https://mlsanity.com/paper/2502.18864/) (2025)
- [SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam?](https://mlsanity.com/paper/2507.05241/) (2025)
- [Automated Statistical Model Discovery with Language Models](https://mlsanity.com/paper/2402.17879/) (2024)
- [Scientific production in the era of Large Language Models](https://mlsanity.com/paper/2601.13187/) (2026)
- [SciSciGPT: Advancing Human-AI Collaboration in the Science of Science](https://mlsanity.com/paper/2504.05559/) (2025)
- [Accelerating Clinical Evidence Synthesis with Large Language Models](https://mlsanity.com/paper/2406.17755/) (2024)
- [Exploring the use of AI authors and reviewers at Agents4Science](https://mlsanity.com/paper/2511.15534/) (2025)
- [Can Theoretical Physics Research Benefit from Language Agents?](https://mlsanity.com/paper/2506.06214/) (2025)
- [CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics](https://mlsanity.com/paper/2508.18124/) (2025)
- [Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery](https://mlsanity.com/paper/2603.04735/) (2026)
- [CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers](https://mlsanity.com/paper/2510.05228/) (2025)
- [QMBench: A Research Level Benchmark for Quantum Materials Research](https://mlsanity.com/paper/2512.19753/) (2025)

## Built on by (most cited first, 1 of 1)

- [Agentic Publication Protocol: An Attempt to Modernize Scientific Publication](https://mlsanity.com/paper/2606.27386/) (2026)

## Abstract (arXiv)

This article argues that the most important significance of the AI revolution, especially the rise of large language models, lies not simply in automation, but in a fundamental change in how complex information and human know-how are carried, replicated, and shared. From this perspective, AI for Science is especially important because it may transform not only the efficiency of research, but also the structure of scientific collaboration, discovery, publishing, and evaluation. The article outlines a gradual path from AI as a research tool to AI as a scientific collaborator, and discusses how AI is likely to fundamentally reshape scientific publication. It also argues that continuous learning and diversity of ideas are essential if AI is to play a meaningful role in original scientific discovery.