Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics

# Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics
Source: [https://arxiv.org/abs/2606.12828](https://arxiv.org/abs/2606.12828)
[View PDF](https://arxiv.org/pdf/2606.12828)

> Abstract:Do research topics in artificial intelligence grow gradually, or do they advance through abrupt, detectable jumps? Analyzing 80,814 accepted main\-track papers from five premier AI conferences \(ACL, CVPR, ICLR, ICML, NeurIPS\) spanning 2017 to 2025, we show major AI topics advance through topical phase transitions: remaining marginal for years, then surging across venues within one to three years\. Large language models became the dominant cross\-venue topic by 2025, diffusion models rose with comparable abruptness, and language\-model methods crossed into computer vision via vision\-language models, whereas reinforcement learning compounded smoothly, distinguishing genuine phase transitions from ordinary growth\. This structure is our primary contribution: a large\-scale, cross\-venue characterization of how AI research reorganizes\. We then ask whether a transition leaves a detectable footprint before it peaks\. We define an early\-warning signature, four publication\-dynamics criteria frozen on 2017\-2021 data, and evaluate it out of sample on 2023\-2025 transitions, obtaining a precision of 27% and recall of 63% against a 13\.5% base rate\. Applied to 2025 data, the signature flags reasoning and test\-time compute, agentic AI, multimodal LLMs, retrieval\-augmented generation, and world models as topics to monitor over 2026\-2028\. The source code is also publicly available on GitHub at[this https URL](https://github.com/KurbanIntelligenceLab/ai-phase-transitions)\.

## Submission history

From: Rasul Khanbayov \[[view email](https://arxiv.org/show-email/df3c5105/2606.12828)\] **\[v1\]**Thu, 11 Jun 2026 02:47:41 UTC \(1,215 KB\)