mlsanityData to 14 Oct 2026

Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection

arXiv 2310.18906 ↗First posted 29 Oct 2023cs.CL cs.AIcited by 3

Not on the map. Why?

Abstract (arXiv)

This paper reports our submission under the team name `SynthDetectives' to the ALTA 2023 Shared Task. We use a stacking ensemble of Transformers for the task of AI-generated text detection. Our approach is novel in terms of its choice of models in that we use accessible and lightweight models in the ensemble. We show that ensembling the models results in an improved accuracy in comparison with using them individually. Our approach achieves an accuracy score of 0.9555 on the official test data provided by the shared task organisers.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 20 of its 25 references that are in the map. First posted on arXiv 29 Oct 2023.

Builds on

20 of 25 references.

References · 20

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,811
  5. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  6. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,850
  7. 2023DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvaturecited by 726
  8. 2019GLTR: Statistical Detection and Visualization of Generated Textcited by 496
  9. 2021MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontierscited by 470
  10. 2020Automatic Detection of Machine Generated Text: A Critical Surveycited by 166
  11. 2019Real or Fake? Learning to Discriminate Machine from Human Generated Textcited by 99
  12. 2021Artificial Text Detection via Examining the Topology of Attention Mapscited by 49
8 more
  1. 2020Neural Deepfake Detection with Factual Structure of Textcited by 41
  2. 2022Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspectivecited by 41
  3. 2022CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learningcited by 33
  4. 2022Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russiancited by 29
  5. 2021Unsupervised and Distributional Detection of Machine-Generated Textcited by 23
  6. 2020Limits of Detecting Text Generated by Large-Scale Language Modelscited by 15
  7. 2021Fingerprinting Fine-tuned Language Models in the Wildcited by 10
  8. 2022DIALOG-22 RuATD Generated Text Detectioncited by 3

Built on by

Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2024A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterizationcited by 19
  2. 2024Unmasking the Imposters: How Censorship and Domain Adaptation Affect the Detection of Machine-Generated Tweetscited by 1
  3. 2025Domain Gating Ensemble Networks for AI-Generated Text Detectioncited by 0