Paper catalogues 13 patterns for coupling language models with rules
Original title: Hybrid AI Patterns: Thirteen Ways to Couple Language Models with Rules, and How to Choose Among Them
It adds five invariants, five failure patterns, and a decision guide based on the authors’ measurements.
A paper defines thirteen patterns for combining a language model with an executable rule language, using the catalogue form from object-oriented design. Four cover data crossing the model–rules boundary, five who controls whom, three how the model joins reasoning, and one how knowledge persists. Five invariants apply to every combination, and five failure patterns name couplings that break them. The decision guide reports cases where a model alone matched or beat the hybrid and what each design cost.
- The catalogue maps overlaps with published hybrid and neuro-symbolic taxonomies.
- Each pattern entry covers intent, participants, consequences, implementation and known uses.
- Measurements include cases where a model alone did as well as or better than a hybrid.
From the original article
1 min read at arxiv.orgLanguage models handle text well, and rule engines give conclusions with proofs. Systems that combine the two are usually described by example, and the same coupling turns up under different names in agent frameworks, guardrail toolkits and neuro-symbolic research.
By Siegfried Handschuh · arxiv.org
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.