# RT-J preprint reports database predictions with 10x fewer examples

_Published Friday, October 16, 2026 at 9:12 AM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers report that RT-J, an 86M-parameter model for predicting outcomes from relational databases, matches strong feature engineering pipelines with 10x fewer examples on average in RelBench in-context regression tasks. The preprint describes predictions made using hundreds of examples or fewer.

The researchers pretrained RT-J on 639 web-crawled databases with 6,023 LLM-generated forecasting tasks, using contexts of up to 8,192 database cells. A lightweight random-walk retriever selects examples, while context tuning and ensembling increase computation at prediction time. The reported comparison concerns regression tasks in RelBench; it does not establish the same reduction across all database prediction workloads.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2610.17867)

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Canonical: https://techandbusiness.org/newswire/xPXTTjRLyRexzUnwI_piAd
Published: 2026-10-16T13:12:44.284Z
Story chronology: 2026-10-16T04:00:00.000Z
Retrieved: 2026-10-16T17:00:51.069Z
Publisher: Tech & Business (techandbusiness.org)