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

被引：0

作者：

Datta, Ayan ^{[1
]}

Chandramania, Aryan ^{[1
]}

Mamidi, Radhika ^{[1
]}

机构：

[1] IIIT Hyderabad, Hyderabad, Telangana, India

来源：

PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024 | 2024年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1623 / 1626

页数：4

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