Autoresearch for Marketplace Catalogs: From Legacy Forms to AI-Native Matching

arXiv cs.AISeptember 2, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2609.00274v1 Announce Type: new Abstract: Two-sided service marketplaces are moving from deterministic request-form intake to AI-native probabilistic matching, enabled by large language models (LLMs) that infer intent, preferences, and latent constraints from natural language. Relying on inferred intent rather than fixed-form fields forces these platforms to regenerate the provider-side preference taxonomy underwriting matching, search, and pricing: attributes interpretable to service providers while remaining a useful signal for marketplace decisions. We present an autoresearch loop that generates this taxonomy, one occupation at a time, and has been deployed in production at a major

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