Universal and Independent: Multilingual Probing Framework for Exhaustive Model Interpretation and Evaluation
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Abstract (arXiv)
Linguistic analysis of language models is one of the ways to explain and describe their reasoning, weaknesses, and limitations. In the probing part of the model interpretability research, studies concern individual languages as well as individual linguistic structures. The question arises: are the detected regularities linguistically coherent, or on the contrary, do they dissonate at the typological scale? Moreover, the majority of studies address the inherent set of languages and linguistic structures, leaving the actual typological diversity knowledge out of scope. In this paper, we present and apply the GUI-assisted framework allowing us to easily probe a massive number of languages for all the morphosyntactic features present in the Universal Dependencies data. We show that reflecting the anglo-centric trend in NLP over the past years, most of the regularities revealed in the mBERT model are typical for the western-European languages. Our framework can be integrated with the existing probing toolboxes, model cards, and leaderboards, allowing practitioners to use and share their standard probing methods to interpret multilingual models. Thus we propose a toolkit to systematize the multilingual flaws in multilingual models, providing a reproducible experimental setup for 104 languages and 80 morphosyntactic features. https://github.com/AIRI-Institute/Probing_framework
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 20 of its 28 references that are in the map. First posted on arXiv 24 Oct 2022.
Builds on
20 of 28 references.
References · 20
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8 more
- 2021Discourse Probing of Pretrained Language Modelscited by 38
- 2018NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networkscited by 31
- 2019LINSPECTOR: Multilingual Probing Tasks for Word Representationscited by 22
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- 2021Probing Multilingual Language Models for Discoursecited by 12
- 2021RuSentEval: Linguistic Source, Encoder Force!cited by 4
- 2022Is neural language acquisition similar to natural? A chronological probing studycited by 3
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Citing papers per year: 2022: 1; 2023: 0; 2024: 2.
3 papers.