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SemEval-2024 Task 8: Weighted Layer Averaging RoBERTa for Black-Box Machine-Generated Text Detection

Year: 2024

Type: preprint

Abstract: This document contains the details of the authors' submission to the proceedings of SemEval 2024's Task 8: Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection Subtask A (monolingual) and B. Detection of machine-generated text is becoming an increasingly important task, with the advent of large language models (LLMs). In this paper, we lay out how using weighted averages of RoBERTa layers lets us capture information about text that is relevant to machine-generated text detection.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2402.15873

Authors: Datta, Ayan, Chandramania, Aryan, Mamidi, Radhika

Institution: International Institute of Information Technology, Hyderabad

Language: English

Topic: Authorship Attribution and Profiling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4392223927

Cites:

Cited by: 1

Related to: 10