On General Language Understanding
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 62 references that are in the map. First posted on arXiv 27 Oct 2023.
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References · 16
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,899
- 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,729
- 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,206
- 2020Beyond Accuracy: Behavioral Testing of NLP models with CheckListcited by 1,006
- 2021Probing Classifiers: Promises, Shortcomings, and Advancescited by 876
- 2021A Survey of Embodied AI: From Simulators to Research Taskscited by 261
- 2018Targeted Syntactic Evaluation of Language Modelscited by 242
- 2020Experience Grounds Languagecited by 242
- 2023Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agentscited by 54
- 2021Grounding 'Grounding' in NLPcited by 44
- 2020To Test Machine Comprehension, Start by Defining Comprehensioncited by 31
4 more
- 2022When a sentence does not introduce a discourse entity, Transformer-based models still sometimes refer to itcited by 23
- 2020(Re)construing Meaning in NLPcited by 16
- 2023Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategycited by 12
- 2022How "open" are the conversations with open-domain chatbots? A proposal for Speech Event based evaluationcited by 3
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