# Text Classification: Zero-Shot, Few-Shot, and LLM-Based Document Categorization
Status: public
Confidence: medium (0.78) (verified)
Last verified: 2026-05-28
Generation: ai_structured

## TL;DR
Text classification assigns labels to documents, sentences, or messages. Durable evidence spans CNN sentence models, efficient bag-of-words baselines, and Transformer pretraining.

## Core Explanation
The task can include spam filtering, topic labeling, sentiment analysis, routing, and policy categorization. Model choice depends on data size, latency, label complexity, and tolerance for errors.

## Detailed Analysis
This repair keeps the article grounded in representative methods and avoids broad claims that one architecture is always best.

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