buzzcode2007/LLM-Self-Detection-Research
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Let's investigate how LLMs distinguish itself from human-written work.
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buzz-lightsnack-2007 39516acf9a add: output results for various models and datasets
2024-12-07 23:45:28 +08:00
data refactor sources data structure 2024-12-03 20:44:38 +08:00
tests add: output results for various models and datasets 2024-12-07 23:45:28 +08:00
.gitignore create a folder for prompts cache 2024-12-04 13:38:49 +08:00
data.ipynb split data segregation into another notebook 2024-12-04 11:41:06 +08:00
dependencies.txt Refactor: Remove Gemini and use Gemma 2024-08-30 23:31:51 +08:00
README.md initial writeup 2024-08-22 09:33:58 +00:00

README.md

LLM-self-detection

Let's investigate how LLMs distinguish itself from human-written work.

The paper seeks to investigate and evaluate the self-detection abilities of language learning models through its architecture and its execution performance. The repository, in particular, will contain experimental data to evaluate the said performance.

This is an extended essay developed for the Computer Science subject in the International Baccalaureate.