On General Language Understanding

被引:0
|
作者
Schlangen, David [1 ]
机构
[1] Univ Potsdam, Computat Linguist, Dept Linguist, Potsdam, Germany
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
Natural Language Processing prides itself to be an empirically-minded, if not outright empiricist field, and yet lately it seems to get itself into essentialist debates on issues of meaning and measurement ("Do Large Language Models Understand Language, And If So, How Much?"). This is not by accident: Here, as everywhere, the evidence underspecifies the understanding. As a remedy, this paper sketches the outlines of a model of understanding, which can ground questions of the adequacy of current methods of measurement of model quality. The paper makes three claims: A) That different language use situation types have different characteristics, B) That language understanding is a multifaceted phenomenon, bringing together individualistic and social processes, and C) That the choice of Understanding Indicator marks the limits of benchmarking, and the beginnings of considerations of the ethics of NLP use.
引用
收藏
页码:8818 / 8825
页数:8
相关论文
共 50 条
  • [1] JGLUE: Japanese General Language Understanding Evaluation
    Kurihara, Kentaro
    Kawahara, Daisuke
    Shibata, Tomohide
    LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2022, : 2957 - 2966
  • [2] JGLUE: Japanese General Language Understanding Evaluation
    Kurihara, Kentaro
    Kawahara, Daisuke
    Shibata, Tomohide
    2022 Language Resources and Evaluation Conference, LREC 2022, 2022, : 2957 - 2966
  • [3] General natural language real understanding's realization
    Lu, Y
    Zhao, H
    Shi, B
    COMPUTER SCIENCE AND TECHNOLOGY IN NEW CENTURY, 2001, : 68 - 71
  • [4] From General Language Understanding to Noisy Text Comprehension
    Kasthuriarachchy, Buddhika
    Chetty, Madhu
    Shatte, Adrian
    Walls, Darren
    APPLIED SCIENCES-BASEL, 2021, 11 (17):
  • [5] Towards General Natural Language Understanding with Probabilistic Worldbuilding
    Saparov, Abulhair
    Mitchell, Tom M.
    TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, 2022, 10 : 325 - 342
  • [6] bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark
    Hardalov, Momchil
    Atanasova, Pepa
    Mihaylov, Todor
    Angelova, Galia
    Simov, Kiril
    Osenova, Petya
    Stoyanov, Ves
    Koychev, Ivan
    Nakov, Preslav
    Radev, Dragomir
    PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023): LONG PAPERS, VOL 1, 2023, : 8733 - 8759
  • [7] PrivacyGLUE: A Benchmark Dataset for General Language Understanding in Privacy Policies
    Shankar, Atreya
    Waldis, Andreas
    Bless, Christof
    Rodriguez, Maria Andueza
    Mazzola, Luca
    APPLIED SCIENCES-BASEL, 2023, 13 (06):
  • [8] Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks
    Zhang, Xinsong
    Zeng, Yan
    Zhang, Jipeng
    Li, Hang
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS - EMNLP 2023, 2023, : 551 - 568
  • [9] A GENERAL FRAMEWORK FOR BUILDING NATURAL LANGUAGE UNDERSTANDING MODULES IN VOICE SEARCH
    Feng, Junlan
    2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 5362 - 5365
  • [10] SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
    Wang, Alex
    Pruksachatkun, Yada
    Nangia, Nikita
    Singh, Amanpreet
    Michael, Julian
    Hill, Felix
    Levy, Omer
    Bowman, Samuel R.
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32