AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4
<|reference_start|>AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4: This paper describes AIpom, a system designed to detect a boundary between human-written and machine-generated text (SemEval-2024 Task 8, Subtask C: Human-Machine Mixed Text Detection). We propose a two-stage pipeline combining predictions from an instruction-tuned decoder-only model and encoder-only sequence taggers. AIpom is ranked second on the leaderboard while achieving a Mean Absolute Error of 15.94. Ablation studies confirm the benefits of pipelining encoder and decoder models, particularly in terms of improved performance.<|reference_end|>
@article{shirnin2024aipom,
    title={AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4},
    author={Alexander Shirnin, Nikita Andreev, Vladislav Mikhailov, Ekaterina
  Artemova},
    journal={arXiv preprint arXiv:2403.19354},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.19354},
    primaryClass={cs.CL}
}