benchmarks evals
The Table Model Interpolated Physics but Lost the Units
Four tabular foundation models beat six baselines on samples from 316 equations yet could not represent noiseless mechanisms or physical units.
Summary
Four tabular foundation models beat six baselines on samples from 316 equations yet could not represent noiseless mechanisms or physical units.
The study treats table completion as a probe of what physics-like priors tabular foundation models acquire. Across in-domain and out-of-domain datasets sampled from 316 equations, the four tested systems led the baselines before and after tuning. The authors' central negative result is that those priors still cannot encode a deterministic mechanism or units, so strong interpolation should not be confused with a physical model.
Why it matters
Four tabular foundation models beat six baselines on samples from 316 equations yet could not represent noiseless mechanisms or physical units.
Limits and context
- The authors' central negative result is that those priors still cannot encode a deterministic mechanism or units, so strong interpolation should not be confused with a physical model.
Key claims
Four tabular foundation models beat six baselines on samples from 316 equations yet could not represent noiseless mechanisms or physical units.
Qualification: The authors' central negative result is that those priors still cannot encode a deterministic mechanism or units, so strong interpolation should not be confused with a physical model.
Evidence: source-2026-09-03-006
Sources
- arXiv preprint 2609.02766arXiv · primary research
Corrections
No corrections have been recorded for this story.