---
license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - ai-generated-text-detection
  - generator-shift
size_categories:
  - 10K<n<100K
---

> **Single-class dataset.** Every row is AI-generated (`Is_AI = 1`). It is
> designed to measure generator shift and must be paired with human text, e.g.
> the human side of HC3 PLUS, to form a balanced detection benchmark.
# HC3 Gemini 2.0 Flash Responses
 
## Dataset Description
 
This dataset contains **{len(df_upload):,} AI-generated text samples** produced by 
**Google Gemini 2.0 Flash** in response to questions from the 
[HC3 (Human ChatGPT Comparison Corpus)](https://huggingface.co/datasets/Hello-SimpleAI/HC3) benchmark.
 
It was constructed to evaluate AI-generated text detectors on out-of-distribution 
generator transfer — specifically, testing whether detectors trained on other generators 
(ChatGPT, LLaMA, etc.) can detect Gemini-generated text without retraining.
 
## Usage
 
```python
from datasets import load_dataset
ds = load_dataset("mohamedmady/HC3-Gemini-Flash-Responses")
```
 
## Dataset Details
 
| Property | Value |
|---|---|
| Samples | {len(df_upload):,} |
| Generator | Gemini 2.0 Flash |
| Source questions | HC3 benchmark |
| Domain | Question Answering (QA) |
| Language | English |
| Label | All AI-generated (label=1) |
 
## Column Schema
 
| Column | Type | Description |
|---|---|---|
| `text` | string | AI-generated response text |
| `label` | ClassLabel | 1 = AI-generated, 0 = Human |
| `source` | string | Generator model (`gemini-2.0-flash`) |
| `domain` | string | Text domain (`qa`) |
| `split` | string | Dataset split (`test`) |
 
## Context and Citation
 
This dataset was created for the paper:
 
> **DeBERTa-ConPara: Robust AI-Generated Text Detection under Adversarial and 
> Cross-Domain Conditions** (EMNLP 2026 submission)
 
DeBERTa-ConPara v2.4-3k achieves **98.64% AI recall** on this dataset under 
fixed-threshold evaluation (τ*=0.920), demonstrating strong cross-generator 
generalization to Gemini outputs without any Gemini training data.
 
```bibtex
@misc{{Mady25-GeminiHC3,
  author = {{Mady, Mohamed}},
  title  = {{HC3 Gemini 2.0 Flash Responses}},
  year   = {{2025}},
  url    = {{https://huggingface.co/datasets/mohamedmady/HC3-Gemini-Flash-Responses}},
  note   = {{Hugging Face dataset}}
}}
```
 
## License
 
CC-BY-4.0. The source HC3 questions are from 
[Hello-SimpleAI/HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3).
Responses were generated by the authors using the Gemini 2.0 Flash API.
"""