paper-humanizer

name

paper-humanizer

description

Academic text polisher and humanizer for Chinese and English research writing. Removes AI-like patterns while preserving factual accuracy. Use when polishing academic text, reducing AI-generated patterns in papers/theses, improving naturalness of research writing while maintaining data integrity, or enhancing scholarly tone without fabricating facts. Supports both Chinese (中文) and English academic texts with configurable tone, field-specific terminology, and strict factuality controls.

Paper Humanizer

Polish and humanize academic writing to reduce AI-like patterns while preserving all factual content, data, and meaning.

Quick Start

Apply the system prompt from references/system_prompt.md and use the workflow below.

Output Format

Always produce exactly 4 sections:

1. 原文 AI 特征分析 (Original Text AI Pattern Analysis)
2. 核心优化策略 (Core Optimization Strategies)
3. 优化亮点说明 (Highlight Notes - optional)
4. 优化后的文章 (Polished Text - full revised text)

Core Constraints

Non-negotiable:

• Never fabricate facts, results, metrics, or references
• Never change numeric values, experimental settings, or data
• Preserve citation markers (e.g., [1], (Smith, 2023), \cite{...})
• Maintain all terminology and technical accuracy

Remove AI-isms:

• Chinese: "值得注意的是", "不难发现", "基于以上分析", "综上所述", "首先/其次/最后", "本文将"
• English: "It is worth noting that", "It can be seen that", "In summary", "Firstly, Secondly, Finally" (when overused)

See references/phrase_blacklist.md for complete list.

Parameters

Configure behavior using these parameters:

• language: auto (detect) | zh (Chinese) | en (English)
• tone: formal (default) | semi-formal | concise | persuasive
• strict_factuality: true (default) - preserve all data/facts
• keep_citations: true (default) - preserve citation markers
• blacklist_level: high (default) | medium | low

Workflow

1. Analyze: Identify 2-3 major AI pattern issues in the input text
2. Strategy: Decide 3-5 targeted optimization strategies
3. Execute: Apply edits while strictly preserving factual content
4. Output: Deliver the 4-section format with full polished text

Language Handling

• Auto-detect language from input text
• Maintain same language in output (unless user requests translation)
• Keep technical terms (GAN, WGAN-GP, NSL-KDD) as-is
• Preserve field-specific terminology

Advanced Features

For domain-specific terminology or special requirements, see:

• references/system_prompt.md - Complete editing principles and constraints
• references/phrase_blacklist.md - AI-pattern phrases to avoid
• references/user_template.md - Parameterized user prompt template

Script Usage (Optional)

Use the CLI wrapper for batch processing:

# Process a text file
python3 scripts/paper_humanizer.py --text-file input.txt --language auto

# Generate composed prompt for external use
python3 scripts/paper_humanizer.py --text-file input.txt --out prompt.md

The script combines system prompt and user template with specified parameters.