The next step in
artificial text detection

The next step in artificial text detection

The next step in artificial text detection

NLP researchers and industry practitioners are seeking new benchmarks to detect artificial text. A joint project of MIT Lincoln Laboratory, Penn State University, University of Oslo, and Toloka proposes a novel approach to artificial text detectors. Contribute to building the benchmark, or use it for your NLP and GenAI projects.

What makes the benchmark different?

The new benchmark compares LLM-generated texts to human-edited versions. Texts cover a range of use cases from creating writing to summarizing news articles.

The new benchmark compares LLM-generated texts to human-edited versions. Texts cover a range of use cases from creating writing to summarizing news articles.

How can I contribute to the benchmark?

1

Make edits

Edit the model's output to make it sound more human — change, remove, or add text to align with your preferences.

2

Submit the new version of the text

3

Access the benchmark when it's ready to use

1

2

3

Make edits

Edit the model's output to make it sound more human — change, remove, or add text to align with your preferences.

Submit the new
version of the text

Access the benchmark
when it's ready to use

Start

Start

Sign up to access the benchmark

Leave your email, and you'll be the first to know when the benchmark is ready. You can use it to build and test next-generation artificial text detectors

Sign up

Sign up to access the benchmark

Leave your email, and you'll be the first to know when the benchmark is ready. You can use it to build and test next-generation artificial text detectors

Sign up

Sign up to access the benchmark

Leave your email, and you'll be the first to know when the benchmark is ready. You can use it to build and test next-generation artificial text detectors

Sign up

How can I contribute to the benchmark?

Start

Start

1

Make edits

Edit the model's output to make it sound more human — change, remove, or add text to align with your preferences.

2

Submit the new version of the text

3

Access the benchmark when it's ready to use

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