arXiv Artificial Intelligence

SAFAARI: Schema-Aware Framework for Accelerated Advertiser Response Intelligence

SAFAARI: Schema-Aware Framework for Accelerated Advertiser Response Intelligence

Quick summary

arXiv:2607.25042v1 Announce Type: new Abstract: The evolution of customer support systems is rapidly advancing with agentic chatbots, yet these systems face significant limitations when accessing enterprise data without predefined API endpoints. This paper presents SAFAARI (Schema-Aware Framework for Accelerated Advertiser Response Intelligence), a multi-agent framework that addresses the critical bottleneck of schema linking in Natural Language to SQL (NL-to-SQL) systems through specialized content, metadata, and orchestration agents. We also introduce SEAL (Schema Evaluation and Accuracy in

Key takeaways

  • arXiv:2607.25042v1 Announce Type: new Abstract: The evolution of customer support systems is rapidly advancing with agentic chatbots, yet these systems face significant limitations when accessing enterprise data without predefined API endpoints.
  • This paper presents SAFAARI (Schema-Aware Framework for Accelerated Advertiser Response Intelligence), a multi-agent framework that addresses the critical bottleneck of schema linking in Natural Language to SQL (NL-to-SQL) systems through specialized content, metadata, and orchestration agents.
  • We also introduce SEAL (Schema Evaluation and Accuracy in

Why it matters

“SAFAARI: Schema-Aware Framework for Accelerated Advertiser Response Intelligence” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗