LLM Routing as Reasoning: A MaxSAT View
Routing a query through an appropriate LLM is challenging, particularly when user preferences are expressed in natural language and model attributes are only partially observable. We propose a constraint-based interpretation of language-conditioned LLM routing, formulating it as a weighted MaxSAT/MaxSMT problem in which natural language feedback induces hard and soft constraints over model attributes. Under this view, routing corresponds to selecting models that approximately maximize satisfaction of feedback-conditioned clauses. Empirical analysis on a 25-model benchmark shows that language feedback produces near-feasible recommendation sets, while no-feedback scenarios reveal systematic...
| Authors | Son Nguyen, Xinyuan Liu, Ransalu Senanayake |
|---|---|
| Primary category | cs.AI |
| Published | 13 March 2026 |
| Last updated at source | 13 March 2026 |
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