mlsanityData to 7 Oct 2026

The Agentification of Scientific Research: A Physicist's Perspective

arXiv 2604.14718 ↗First posted 16 Apr 2026cs.AI cond-mat.dis-nn hep-thcited by 1

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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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 16 Apr 2026.

Builds on

14 of 31 references.

References · 14

  1. 2023ChemCrow: Augmenting large-language models with chemistry toolscited by 609
  2. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 405
  3. 2025Accelerating scientific discovery with Co-Scientistcited by 353
  4. 2025SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam?cited by 45
  5. 2024Automated Statistical Model Discovery with Language Modelscited by 41
  6. 2026Scientific production in the era of Large Language Modelscited by 30
  7. 2025SciSciGPT: Advancing Human-AI Collaboration in the Science of Sciencecited by 26
  8. 2024Accelerating Clinical Evidence Synthesis with Large Language Modelscited by 15
  9. 2025Exploring the use of AI authors and reviewers at Agents4Sciencecited by 13
  10. 2025Can Theoretical Physics Research Benefit from Language Agents?cited by 9
  11. 2025CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physicscited by 9
  12. 2026Solving an Open Problem in Theoretical Physics using AI-Assisted Discoverycited by 7
2 more
  1. 2025CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researcherscited by 4
  2. 2025QMBench: A Research Level Benchmark for Quantum Materials Researchcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.