mlsanityData to 14 Oct 2026

LLMs Learn Constructions That Humans Do Not Know

arXiv 2508.16837 ↗First posted 22 Aug 2025cs.CLcited by 1

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Abstract (arXiv)

This paper investigates false positive constructions: grammatical structures which an LLM hallucinates as distinct constructions but which human introspection does not support. Both a behavioural probing task using contextual embeddings and a meta-linguistic probing task using prompts are included, allowing us to distinguish between implicit and explicit linguistic knowledge. Both methods reveal that models do indeed hallucinate constructions. We then simulate hypothesis testing to determine what would have happened if a linguist had falsely hypothesized that these hallucinated constructions do exist. The high accuracy obtained shows that such false hypotheses would have been overwhelmingly confirmed. This suggests that construction probing methods suffer from a confirmation bias and raises the issue of what unknown and incorrect syntactic knowledge these models also possess.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 22 Aug 2025.

Builds on

17 of 27 references.

References · 17

  1. 2020Universal Dependencies v2: An Evergrowing Multilingual Treebank Collectioncited by 271
  2. 2022Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?cited by 113
  3. 2024Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNscited by 65
  4. 2024Frequency Explains the Inverse Correlation of Large Language Models' Size, Training Data Amount, and Surprisal's Fit to Reading Timescited by 39
  5. 2022The Better Your Syntax, the Better Your Semantics? Probing Pretrained Language Models for the English Comparative Correlativecited by 35
  6. 2020CxGBERT: BERT meets Construction Grammarcited by 32
  7. 2022Neural reality of argument structure constructionscited by 25
  8. 2022When classifying grammatical role, BERT doesn't care about word order... except when it matterscited by 24
  9. 2020Investigating representations of verb bias in neural language modelscited by 22
  10. 2023A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Constructioncited by 22
  11. 2022WinoDict: Probing language models for in-context word acquisitioncited by 15
  12. 2023Construction Grammar Provides Unique Insight into Neural Language Modelscited by 13
5 more
  1. 2023A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding Spacescited by 13
  2. 2024Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasonscited by 13
  3. 2021Finding Variants for Construction-Based Dialectometry: A Corpus-Based Approach to Regional CxGscited by 11
  4. 2021Production vs Perception: The Role of Individuality in Usage-Based Grammar Inductioncited by 6
  5. 2024Large corpora and large language models: a replicable method for automating grammatical annotationcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.