mlsanityData to 7 Oct 2026

How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Context

arXiv 2004.00881 ↗First posted 2 Apr 2020cs.CLcited by 26

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Abstract (arXiv)

We study the influence of context on sentence acceptability. First we compare the acceptability ratings of sentences judged in isolation, with a relevant context, and with an irrelevant context. Our results show that context induces a cognitive load for humans, which compresses the distribution of ratings. Moreover, in relevant contexts we observe a discourse coherence effect which uniformly raises acceptability. Next, we test unidirectional and bidirectional language models in their ability to predict acceptability ratings. The bidirectional models show very promising results, with the best model achieving a new state-of-the-art for unsupervised acceptability prediction. The two sets of experiments provide insights into the cognitive aspects of sentence processing and central issues in the computational modelling of text and discourse.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2020.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 7; 2024: 3; 2025: 1; 2026: 3.

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  1. 2022mGPT: Few-Shot Learners Go Multilingualcited by 141
  2. 2023The Next Chapter: A Study of Large Language Models in Storytellingcited by 58
  3. 2021Artificial Text Detection via Examining the Topology of Attention Mapscited by 49
  4. 2021Grey-box Adversarial Attack And Defence For Sentiment Classificationcited by 28
  5. 2023A Family of Pretrained Transformer Language Models for Russiancited by 27
  6. 2022RuCoLA: Russian Corpus of Linguistic Acceptabilitycited by 26
  7. 2021Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpuscited by 18
  8. 2021DaLAJ - a dataset for linguistic acceptability judgments for Swedish: Format, baseline, sharingcited by 16
  9. 2021Evaluating the Efficacy of Summarization Evaluation across Languagescited by 14
  10. 2024How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgmentscited by 14
  11. 2024A Systematic Assessment of Language Models with Linguistic Minimal Pairs in Chinesecited by 13
  12. 2021Shaking Syntactic Trees on the Sesame Street: Multilingual Probing with Controllable Perturbationscited by 10
14 more
  1. 2024What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Lengthcited by 10
  2. 2023DeltaScore: Fine-Grained Story Evaluation with Perturbationscited by 9
  3. 2023Second Language Acquisition of Neural Language Modelscited by 8
  4. 2022Testing the limits of natural language models for predicting human language judgmentscited by 7
  5. 2022Template-based Approach to Zero-shot Intent Recognitioncited by 5
  6. 2023Can BERT eat RuCoLA? Topological Data Analysis to Explaincited by 5
  7. 2023Multilingual Nonce Dependency Treebanks: Understanding how Language Models represent and process syntactic structurecited by 5
  8. 2021Language Model Evaluation in Open-ended Text Generationcited by 2
  9. 2026Predicting Sentence Acceptability Judgments in Multimodal Contextscited by 1
  10. 2022NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries?cited by 0
  11. 2023Unsupervised Paraphrasing of Multiword Expressionscited by 0
  12. 2025Do Large Language Models know who did what to whom?cited by 0
  13. 2026Finding Sense in Nonsense with Generated Contexts: Perspectives from Humans and Language Modelscited by 0
  14. 2026LLM and Human Modes of Representationcited by 0