mlsanityData to 7 Oct 2026

Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition

arXiv 1902.10618 ↗First posted 27 Feb 2019cs.CLcited by 27

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Abstract (arXiv)

Building meaningful phrase representations is challenging because phrase meanings are not simply the sum of their constituent meanings. Lexical composition can shift the meanings of the constituent words and introduce implicit information. We tested a broad range of textual representations for their capacity to address these issues. We found that as expected, contextualized word representations perform better than static word embeddings, more so on detecting meaning shift than in recovering implicit information, in which their performance is still far from that of humans. Our evaluation suite, including 5 tasks related to lexical composition effects, can serve future research aiming to improve such representations.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2019.

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Citing papers per year: 2021: 4; 2022: 8; 2023: 6; 2024: 5; 2025: 3; 2026: 1.

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  1. 2021Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Docited by 178
  2. 2022Understanding Transformer Memorization Recall Through Idiomscited by 62
  3. 2021It's not Rocket Science : Interpreting Figurative Language in Narrativescited by 39
  4. 2022SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embeddingcited by 36
  5. 2022Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translationcited by 28
  6. 2021AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Modelscited by 27
  7. 2023IRFL: Image Recognition of Figurative Languagecited by 23
  8. 2025Jawaher: A Multidialectal Dataset of Arabic Proverbs for LLM Benchmarkingcited by 18
  9. 2024Scope Ambiguities in Large Language Modelscited by 11
  10. 2024Semantics of Multiword Expressions in Transformer-Based Models: A Surveycited by 9
  11. 2023A Psycholinguistic Analysis of BERT's Representations of Compoundscited by 7
  12. 2024Generative linguistics contribution to artificial intelligence: Where this contribution lies?cited by 7
15 more
  1. 2024What fifty-one years of Linguistics and Artificial Intelligence research tell us about their correlation: A scientometric analysiscited by 7
  2. 2022Sample Efficient Approaches for Idiomaticity Detectioncited by 3
  3. 2023Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Spacecited by 3
  4. 2022Multilingual Extraction and Categorization of Lexical Collocations with Graph-aware Transformerscited by 2
  5. 2025Is a Peeled Apple Still Red? Evaluating LLMs' Ability for Conceptual Combination with Property Typecited by 2
  6. 2022UAlberta at SemEval 2022 Task 2: Leveraging Glosses and Translations for Multilingual Idiomaticity Detectioncited by 1
  7. 2023Language Cognition and Language Computation -- Human and Machine Language Understandingcited by 1
  8. 2023Agentivit`a e telicit`a in GilBERTo: implicazioni cognitivecited by 1
  9. 2024Investigating Idiomaticity in Word Representationscited by 1
  10. 2021Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoderscited by 0
  11. 2022HiJoNLP at SemEval-2022 Task 2: Detecting Idiomaticity of Multiword Expressions using Multilingual Pretrained Language Modelscited by 0
  12. 2022NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries?cited by 0
  13. 2023Compositional Fusion of Signals in Data Embeddingcited by 0
  14. 2025Attention on Multiword Expressions: A Multilingual Study of BERT-based Models with Regard to Idiomaticity and Microsyntaxcited by 0
  15. 2026Controlled Paraphrase Geometry in Sentence Embedding Space: Local Manifold Modeling and Latent Probingcited by 0