Team lm-detector at PAN: Can NLI be an Appropriate Approach to Machine-Generated Text Detection

被引:0
|
作者
Wu, Guojun [1 ]
Guan, Qinghao [1 ]
机构
[1] University of Zurich, Zurich,8050, Switzerland
来源
CEUR Workshop Proceedings | 2024年 / 3740卷
关键词
Language inference - Logical consistency - Machine-generated text detection - Machine-generated texts - Natural language inference - Natural languages - Novel methods - Online security - Text detection - Theoretical foundations;
D O I
暂无
中图分类号
学科分类号
摘要
18
引用
收藏
页码:2956 / 2962
相关论文
共 35 条
  • [1] MAGE: Machine-generated Text Detection in the Wild
    Li, Yafu
    Li, Qintong
    Cui, Leyang
    Bi, Wei
    Wang, Zhilin
    Wang, Longyue
    Yang, Linyi
    Shi, Shuming
    Zhang, Yue
    PROCEEDINGS OF THE 62ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 1: LONG PAPERS, 2024, : 36 - 53
  • [2] Detection of Machine-Generated Text: Literature Survey
    University of Arkansas at Little Rock, United States
    arXiv,
  • [3] IMGTB: A Framework for Machine-Generated Text Detection Benchmarking
    Spiegel, Michal
    Macko, Dominik
    PROCEEDINGS OF THE 62ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 3: SYSTEM DEMONSTRATIONS, 2024, : 172 - 179
  • [4] Team AT at SemEval-2024 Task 8: Machine-Generated Text Detection with Semantic Embeddings
    Wei, Yuchen
    PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024, 2024, : 492 - 496
  • [5] RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
    Dugan, Liam
    Ippolito, Daphne
    Kirubarajan, Arun
    Callison-Burch, Chris
    PROCEEDINGS OF THE 2020 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING: SYSTEM DEMONSTRATIONS, 2020, : 189 - 196
  • [6] Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
    Crothers, Evan N.
    Japkowicz, Nathalie
    Viktor, Herna L.
    IEEE ACCESS, 2023, 11 : 70977 - 71002
  • [7] NewbieML at SemEval-2024 Task 8: Ensemble Approach for Multidomain Machine-Generated Text Detection
    Tran, Bao
    Nhi Tran
    PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024, 2024, : 354 - 360
  • [8] MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark
    Macko, Dominik
    Moro, Robert
    Uchendu, Adaku
    Lucas, Jason Samuel
    Yamashita, Michiharu
    MatusPikuliak
    Srba, Ivan
    Le, Thai
    Lee, Dongwon
    Simko, Jakub
    Bielikova, Maria
    2023 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2023), 2023, : 9960 - 9987
  • [9] Self-Information Loss Compensation Learning for Machine-Generated Text Detection
    Wang, Weikuan
    Feng, Ao
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2021, 2021
  • [10] Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains
    Mikael Sarvazyan, Areg
    Angel Gonzalez, Jose
    Franco-Salvador, Marc
    Rangel, Francisco
    Chulvi, Berta
    Rosso, Paolo
    PROCESAMIENTO DEL LENGUAJE NATURAL, 2023, (71): : 275 - 288