IdeaTaste: Do LLMs Share the Research Taste of Human Researchers?
- Published
- Source
- arXiv
- Paper number
- 1426
- Field
- Research
- arXiv ID
- 2611.03424
Key points
- The authors measured research taste by collecting more than 90,000 proposals from six language models across four research areas.
- LLM agents reached about 26% of the human level on citation matching and only 18% on idea matching.
- Each LLM agent worked within a budget of 20 steps, and each population held 300 proposals written in two rounds of 150.
- The authors state that two models trained before 2026 cannot have seen any 2026 paper, so their results are free of leakage by construction.
- In blinded expert review, AI proposals scored below the 2026 papers on every quality dimension, by 20 points on expected success.
- The authors conclude the bottleneck lies less in knowing what to work on than in deciding how to pursue it.
Paper links
External research summaries. These are not HDATF publications or measured product results.