# Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection

arXiv: https://arxiv.org/abs/2410.14875 · HTML: https://mlsanity.com/paper/2410.14875/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 8 references that are in the map.
- First posted on arXiv 18 Oct 2024.

## Builds on (most cited first, 4 of 4)

- [OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples](https://mlsanity.com/paper/2307.11729/) (2023)
- [LibAUC: A Deep Learning Library for X-Risk Optimization](https://mlsanity.com/paper/2306.03065/) (2023)
- [TextDescriptives: A Python package for calculating a large variety of metrics from text](https://mlsanity.com/paper/2301.02057/) (2023)
- [Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection](https://mlsanity.com/paper/2402.00412/) (2024)

## Built on by (most cited first, 2 of 2)

- [PhantomHunter: Detecting Unseen Privately-Tuned LLM-Generated Text via Family-Aware Learning](https://mlsanity.com/paper/2506.15683/) (2025)
- [DACTYL: Diverse Adversarial Corpus of Texts Yielded from Large Language Models](https://mlsanity.com/paper/2508.00619/) (2025)

## Abstract (arXiv)

As LLMs increase in accessibility, LLM-generated texts have proliferated across several fields, such as scientific, academic, and creative writing. However, LLMs are not created equally; they may have different architectures and training datasets. Thus, some LLMs may be more challenging to detect than others. Using two datasets spanning four total writing domains, we train AI-generated (AIG) text classifiers using the LibAUC library - a deep learning library for training classifiers with imbalanced datasets. Our results in the Deepfake Text dataset show that AIG-text detection varies across domains, with scientific writing being relatively challenging. In the Rewritten Ivy Panda (RIP) dataset focusing on student essays, we find that the OpenAI family of LLMs was substantially difficult for our classifiers to distinguish from human texts. Additionally, we explore possible factors that could explain the difficulties in detecting OpenAI-generated texts.