AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 17 references that are in the map. First posted on arXiv 28 Mar 2024.
Builds on
9 of 17 references.
References · 9
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.