AI RESEARCH
From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning
arXiv CS.LG
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ArXi:2603.16901v1 Announce Type: new Function-calling language models are essential for agentic AI systems that translate natural language into executable structured actions, yet existing models exhibit severe structural instability when applied to Arabic. We present AISA-AR-FunctionCall, a production-oriented Arabic function-calling framework built on a 270M-parameter FunctionGemma backbone and trained through systematic dataset auditing, schema repair, tool-aware prompt restructuring, and full-parameter supervised fine-tuning.