AI RESEARCH
TableMind++: An Uncertainty-Aware Programmatic Agent for Tool-Augmented Table Reasoning
arXiv CS.CL
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ArXi:2603.07528v1 Announce Type: new Table reasoning requires models to jointly perform semantic understanding and precise numerical operations. Most existing methods rely on a single-turn reasoning paradigm over tables which suffers from context overflow and weak numerical sensitivity. To address these limitations, we previously proposed TableMind as a tuning-based autonomous programmatic agent that simulates human-like interaction within a lightweight large language model (LLM). TableMind internalizes planning, action, and reflection through a two-stage.