mlsanityData to 7 Oct 2026

Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items

arXiv 1808.10627 ↗First posted 31 Aug 2018cs.CLcited by 36

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Abstract (arXiv)

In this paper, we attempt to link the inner workings of a neural language model to linguistic theory, focusing on a complex phenomenon well discussed in formal linguis- tics: (negative) polarity items. We briefly discuss the leading hypotheses about the licensing contexts that allow negative polarity items and evaluate to what extent a neural language model has the ability to correctly process a subset of such constructions. We show that the model finds a relation between the licensing context and the negative polarity item and appears to be aware of the scope of this context, which we extract from a parse tree of the sentence. With this research, we hope to pave the way for other studies linking formal linguistics to deep learning.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2018.

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Citing papers per year: 2021: 14; 2022: 3; 2023: 4; 2024: 6; 2025: 6; 2026: 3.

36 papers.

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  1. 2021Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Littlecited by 176
  2. 2022State-of-the-art generalisation research in NLP: A taxonomy and reviewcited by 97
  3. 2021Understanding by Understanding Not: Modeling Negation in Language Modelscited by 73
  4. 2025MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairscited by 65
  5. 2024Filtered Corpus Training (FiCT) Shows that Language Models can Generalize from Indirect Evidencecited by 35
  6. 2024Benchmarks as Microscopes: A Call for Model Metrologycited by 33
  7. 2021A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humanscited by 32
  8. 2021Local Interpretations for Explainable Natural Language Processing: A Surveycited by 31
  9. 2021Language Models Use Monotonicity to Assess NPI Licensingcited by 30
  10. 2024On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMscited by 24
  11. 2025Can Language Models Learn Typologically Implausible Languages?cited by 23
  12. 2023This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Modelscited by 18
24 more
  1. 2023MELA: Multilingual Evaluation of Linguistic Acceptabilitycited by 13
  2. 2023Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semanticscited by 11
  3. 2021Language Modelling as a Multi-Task Problemcited by 10
  4. 2021Can RNNs learn Recursive Nested Subject-Verb Agreements?cited by 9
  5. 2025TurBLiMP: A Turkish Benchmark of Linguistic Minimal Pairscited by 9
  6. 2022Leveraging Affirmative Interpretations from Negation Improves Natural Language Understandingcited by 7
  7. 2021Schr"odinger's Tree -- On Syntax and Neural Language Modelscited by 6
  8. 2021John praised Mary because he? Implicit Causality Bias and Its Interaction with Explicit Cues in LMscited by 5
  9. 2025Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understandingcited by 5
  10. 2025A Comprehensive Taxonomy of Negation for NLP and Neural Retrieverscited by 4
  11. 2021Attention vs non-attention for a Shapley-based explanation methodcited by 3
  12. 2025Making Language Models Robust Against Negationcited by 3
  13. 2021Explaining a Neural Attention Model for Aspect-Based Sentiment Classification Using Diagnostic Classificationcited by 1
  14. 2023Counteracts: Testing Stereotypical Representation in Pre-trained Language Modelscited by 1
  15. 2024LLMs' morphological analyses of complex FST-generated Finnish wordscited by 1
  16. 2021Recoding latent sentence representations -- Dynamic gradient-based activation modification in RNNscited by 0
  17. 2021Transformers in the loop: Polarity in neural models of languagecited by 0
  18. 2021Connecting degree and polarity: An artificial language learning studycited by 0
  19. 2022Assessing the Limits of the Distributional Hypothesis in Semantic Spaces: Trait-based Relational Knowledge and the Impact of Co-occurrencescited by 0
  20. 2024Black Big Boxes: Tracing Adjective Order Preferences in Large Language Modelscited by 0
  21. 2024Probing structural constraints of negation in Pretrained Language Modelscited by 0
  22. 2026Thunder-KoNUBench: A Corpus-Aligned Benchmark for Korean Negation Understandingcited by 0
  23. 2026Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networkscited by 0
  24. 2026Exposure is Optional: Learning Unlike Coordination in Language Modelscited by 0