AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4
Alexander Shirnin Nikita Andreev Vladislav Mikhailov Ekaterina Artemova
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.