LEMMA: Learned Guidance for Evidence-Carrying Long-Horizon Symbolic Rewriting
LEMMA is a neuro-symbolic system for long-horizon symbolic mathematical rewriting. It combines a symbolic rule engine, guardrail-filtered action generation, evidence-typed verification, and learned policy guidance to transform a starting expression into a specified goal through individually validated rewrite steps.The accompanying study evaluates six search and decoding procedures on a frozen 120-problem benchmark with reference derivations of depths 64, 96, and 128. On the 89 problems containing genuine branching decisions, learned local action ranking substantially improves fixed-budget search efficiency.
Authors
- Pushp Kharat (ORCID: https://orcid.org/0009-0006-1920-8954)
- Atul Saxena (ORCID: https://orcid.org/0009-0000-3588-9848)
Institutions
- Kubota (Japan) (JP)
- SciGenom Labs (India) (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-19
- DOI
- https://doi.org/10.5281/zenodo.22842819
- Primary Topic
- Mathematics, Computing, and Information Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00