From Prompts to Trees: Effective LLM-Guided Tree Generation for Few-Shot Tabular Classification

Paper recorded by Signals 4 on 2026-10-07 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-07 on arXiv · recorded by Signals 4 on 2026-10-08

Category: cs.CL · 自然语言处理 · first seen 2026-10-08

Abstract

While Large Language Models (LLMs) possess rich world knowledge and impressive generalization capabilities, their direct application to tabular data classification is hindered by high inference costs and limited interpretability. In contrast, decision trees are fast and transparent but often underperform in low-data regimes. In this work, we propose a novel framework that bridges these paradigms b

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