humanizer
ai-humanizer-benchmark
AI Humanizer Benchmark: AI humanizers tested against 7 AI detectors (October 2026)
AI Humanizer Benchmark measures how well AI humanizers rewrite AI-generated text so that AI detectors classify it as human-written, and how much meaning and readability the rewrite loses. In each monthly cycle, 11 AI humanizers rewrite the same 33 source texts across 7 writing categories, using each tool's default settings. Each output gets three kinds of score: 7 AI detectors (GPTZero… See the full description on the dataset page: https://huggingface.co/datasets/ai-humanizer-benchmark/ai-humanizer-benchmark.humanizer-5m
Humanizer-5M
Version: 2.0.0
Humanizer-5M is a synthetic conversational adaptation dataset.
The central objective is not simply to rewrite text to sound casual.
Each example models:
what the user explicitly asks,
what the user may implicitly need,
the user's conversational signals,
the appropriate response calibration,
the final response,
quality and stability metrics.
The dataset specifically teaches proportional adaptation.
High user energy does not automatically mean high… See the full description on the dataset page: https://huggingface.co/datasets/Lelonthecodeur/humanizer-5m.humanizerbench
HumanizerBench: AI humanizer rankings and public audit record
The complete audit record of HumanizerBench, a monthly benchmark of AI humanizers. Every tool rewrites the same freshly generated texts on the most undetectable setting it advertises, and every output is scored by five commercial AI detectors alongside meaning preservation and readability. We pay for every tool ourselves. There are no affiliate deals and no vendor-supplied numbers.
Every input, every humanized output… See the full description on the dataset page: https://huggingface.co/datasets/HumanizerBench/humanizerbench.gohumanize-open-humanizer-dataset
GoHumanize Open Humanizer Dataset
2,957 training pairs and 300 test pairs for teaching a language model to rewrite
AI-styled English prose into natural human writing. Each pair is:
input: a passage rewritten by a large language model in the register typical of LLM output
(formal, smooth, hedged, connective phrases, no contractions);
output: the original human-written passage, from a public-domain book or, since version 2,
from a US federal government publication.
The human… See the full description on the dataset page: https://huggingface.co/datasets/gohumanize/gohumanize-open-humanizer-dataset.ai-humanizer
AI Humanizer Dataset (JSONL)
This dataset is designed for fine-tuning instruction-following LLMs
to rewrite AI-generated text into more natural, human-like language.
Structure
train.jsonl – training split
validation.jsonl – validation split
Format
Each line is a JSON object:
{
"prompt": "Rewrite the following text to sound natural, human-like, and conversational...",
"completion": "Humanized output text here",
"attribution": "Original… See the full description on the dataset page: https://huggingface.co/datasets/KNipun/ai-humanizer.humanizer-data
humanizer-data
Training data for humanizer v2, a 12B model that rewrites AI-written drafts (English and Chinese) so they read like a person wrote them, keeping every fact. Code and app: GitHub. How the data was built, step by step: docs/DATA.md (中文).
Only rows that were actually used to train v2 are here, one config per training step:
Config
Training step
Used in training
With text
Reference only
Removed before release
rewrite_sft
SFT: AI draft → human original
28,560… See the full description on the dataset page: https://huggingface.co/datasets/jialinyyzz/humanizer-data.