# Scientific production in the era of Large Language Models

arXiv: https://arxiv.org/abs/2601.13187 · HTML: https://mlsanity.com/paper/2601.13187/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 39 references that are in the map.
- First posted on arXiv 19 Jan 2026.

## Builds on (most cited first, 12 of 12)

- [Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers](https://mlsanity.com/paper/2409.04109/) (2024)
- [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://mlsanity.com/paper/2302.06590/) (2023)
- [Can large language models provide useful feedback on research papers? A large-scale empirical analysis](https://mlsanity.com/paper/2310.01783/) (2023)
- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction](https://mlsanity.com/paper/2305.09620/) (2023)
- [Large Language Models Reflect Human Citation Patterns with a Heightened Citation Bias](https://mlsanity.com/paper/2405.15739/) (2024)
- [Promotional Language and the Adoption of Innovative Ideas in Science](https://mlsanity.com/paper/2406.02798/) (2024)
- [Where there's a will there's a way: ChatGPT is used more for science in countries where it is prohibited](https://mlsanity.com/paper/2406.11583/) (2024)
- [Divergent LLM Adoption and Heterogeneous Convergence Paths in Research Writing](https://mlsanity.com/paper/2504.13629/) (2025)
- [Undermining Mental Proof: How AI Can Make Cooperation Harder by Making Thinking Easier](https://mlsanity.com/paper/2407.14452/) (2024)
- [Who Gets Recommended? Investigating Gender, Race, and Country Disparities in Paper Recommendations from Large Language Models](https://mlsanity.com/paper/2501.00367/) (2024)
- [Biased AI improves human performance but reduces perceived helpfulness](https://mlsanity.com/paper/2508.09297/) (2025)

## Built on by (most cited first, 30 of 32)

- [The Last Human-Written Paper: Agent-Native Research Artifacts](https://mlsanity.com/paper/2604.24658/) (2026)
- [AI for Auto-Research: Roadmap & User Guide](https://mlsanity.com/paper/2605.18661/) (2026)
- [LLM hallucinations in the wild: Large-scale evidence from non-existent citations](https://mlsanity.com/paper/2605.07723/) (2026)
- [SciIntegrity-Bench: A Benchmark for Evaluating Academic Integrity in AI Scientist Systems](https://mlsanity.com/paper/2605.10246/) (2026)
- [Benchmark Illusion: Disagreement among LLMs and Its Scientific Consequences](https://mlsanity.com/paper/2602.11898/) (2026)
- [SciMDR: Advancing Scientific Multimodal Document Reasoning](https://mlsanity.com/paper/2603.12249/) (2026)
- [How Open Must Language Models be to Enable Reliable Scientific Inference?](https://mlsanity.com/paper/2603.26539/) (2026)
- [Agentic Publication Protocol: An Attempt to Modernize Scientific Publication](https://mlsanity.com/paper/2606.27386/) (2026)
- [The Rise of Large Language Models and the Direction and Impact of US Federal Research Funding](https://mlsanity.com/paper/2601.15485/) (2026)
- [Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers](https://mlsanity.com/paper/2603.25638/) (2026)
- [The Agentification of Scientific Research: A Physicist's Perspective](https://mlsanity.com/paper/2604.14718/) (2026)
- [AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions](https://mlsanity.com/paper/2606.22859/) (2026)
- [Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift](https://mlsanity.com/paper/2606.25152/) (2026)
- [The Emerging AI Paper-Review Arms Race: Adversarial Co-Evolution in Scholarly Publishing](https://mlsanity.com/paper/2609.07713/) (2026)
- [Early Evidence of Vibe-Proving with Consumer LLMs: A Case Study on Spectral Region Characterization with ChatGPT-5.2 (Thinking)](https://mlsanity.com/paper/2602.18918/) (2026)
- [Interpretative Interfaces: Designing for AI-Mediated Reading Practices and the Knowledge Commons](https://mlsanity.com/paper/2603.15863/) (2026)
- [An Analysis of Artificial Intelligence Adoption in NIH-Funded Research](https://mlsanity.com/paper/2604.07424/) (2026)
- [Dead Cognitions: A Census of Misattributed Insights](https://mlsanity.com/paper/2604.10288/) (2026)
- [Toward an Engineering of Science: Rebalancing Generation and Verification in the Age of AI](https://mlsanity.com/paper/2605.10425/) (2026)
- [Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment](https://mlsanity.com/paper/2605.24180/) (2026)
- [AI evaluation may bias perceptions: The importance of context in interpreting academic writing](https://mlsanity.com/paper/2605.26662/) (2026)
- [Smaller, Younger, and More Impactful: How AI-Assisted Writing Transforms Research Teams](https://mlsanity.com/paper/2605.27404/) (2026)
- [Rebuttals Move Peer-Review Scores, but Initial-Review Structure Bounds the Movement](https://mlsanity.com/paper/2606.22166/) (2026)
- [What is Left for Us? Second Scholarship Against the Degradation of Research by AI](https://mlsanity.com/paper/2607.04049/) (2026)
- [Scientific exploration, collaboration and labor division in the large language model era](https://mlsanity.com/paper/2607.20923/) (2026)
- [A robust association between LLM use and scientific productivity: Assessing stopping-time selection](https://mlsanity.com/paper/2607.28968/) (2026)
- [Walking through Discussions: A Mobile Visual Analytics System for In-Situ Group Discussion Analysis](https://mlsanity.com/paper/2608.08617/) (2026)
- [ATTRICITE: Training an Open 4B Model for Citation Recovery toward Faithful Attribution](https://mlsanity.com/paper/2609.14248/) (2026)
- [Has Scientific Talent Shifted from Depth to Breadth?Evidence across Papers, Knowledge Inputs, Careers, and Teams](https://mlsanity.com/paper/2609.14425/) (2026)
- [AI in Science: Early Insights](https://mlsanity.com/paper/2609.28504/) (2026)

## Abstract (arXiv)

Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and 246M online accesses to scientific documents. We find: 1) scientists adopting LLMs to draft manuscripts demonstrate a large increase in paper production, ranging from 23.7-89.3% depending on scientific field and author background, 2) LLM use has reversed the relationship between writing complexity and paper quality, leading to an influx of manuscripts that are linguistically complex but substantively underwhelming, and 3) LLM adopters access and cite more diverse prior work, including books and younger, less-cited documents. These findings highlight a stunning shift in scientific production that will likely require a change in how journals, funding agencies, and tenure committees evaluate scientific works.