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:
- 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)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.semeval-1.73.pdf