Team jelarson at SemEval 2024 Task 8: Predicting Boundary Line Between Human and Machine Generated Text

Joseph Larson, Francis Tyers


Abstract
In this paper, we handle the task of building a system that, given a document written first by a human and then finished by an LLM, the system must determine the transition word i.e. where the machine begins to write. We built a system by examining the data for textual anomalies and combining a method of heuristic approaches with a linear regression model based on the text length of each document.
Anthology ID:
2024.semeval-1.73
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
477–484
Language:
URL:
https://aclanthology.org/2024.semeval-1.73
DOI:
10.18653/v1/2024.semeval-1.73
Bibkey:
Cite (ACL):
Joseph Larson and Francis Tyers. 2024. Team jelarson at SemEval 2024 Task 8: Predicting Boundary Line Between Human and Machine Generated Text. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 477–484, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Team jelarson at SemEval 2024 Task 8: Predicting Boundary Line Between Human and Machine Generated Text (Larson & Tyers, SemEval 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.semeval-1.73.pdf
Supplementary material:
 2024.semeval-1.73.SupplementaryMaterial.txt