ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows

Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines. While recent LLM-based approaches show promise for automating such tasks, they often struggle in practice due to ambiguous instructions, complex task structures, and the lack of structured feedback, resulting in syntactically correct but semantically flawed code. To address these challenges, we propose ProfiliTable, an autonomous multi-agent framew

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ethics.ai (12 May 2026), “ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows,” evidence record 4449, https://ethics.ai/record/4449 (originally published by arXiv).

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