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A Survey of Word Embeddings Evaluation Methods

arXiv 1801.09536 ↗First posted 21 Jan 2018cs.CLcited by 26

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Abstract (arXiv)

Word embeddings are real-valued word representations able to capture lexical semantics and trained on natural language corpora. Models proposing these representations have gained popularity in the recent years, but the issue of the most adequate evaluation method still remains open. This paper presents an extensive overview of the field of word embeddings evaluation, highlighting main problems and proposing a typology of approaches to evaluation, summarizing 16 intrinsic methods and 12 extrinsic methods. I describe both widely-used and experimental methods, systematize information about evaluation datasets and discuss some key challenges.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jan 2018.

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Citing papers per year: 2021: 13; 2022: 2; 2023: 6; 2024: 2; 2025: 3.

26 papers.

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  1. 2021PalmTree: Learning an Assembly Language Model for Instruction Embeddingcited by 49
  2. 2024Plurals: A System for Guiding LLMs Via Simulated Social Ensemblescited by 17
  3. 2021WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddingscited by 8
  4. 2021Evaluating Neural Word Embeddings for Sanskritcited by 8
  5. 2023PWESuite: Phonetic Word Embeddings and Tasks They Facilitatecited by 6
  6. 2021Training Cross-Lingual embeddings for Setswana and Sepedicited by 5
  7. 2024Zipfian Whiteningcited by 3
  8. 2021Literature review on vulnerability detection using NLP technologycited by 2
  9. 2021A Survey On Neural Word Embeddingscited by 2
  10. 2021One System to Rule them All: a Universal Intent Recognition System for Customer Service Chatbotscited by 2
  11. 2021Assessing the Effectiveness of Syntactic Structure to Learn Code Edit Representationscited by 1
  12. 2021Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddingscited by 1
14 more
  1. 2022Word Embeddings for Automatic Equalization in Audio Mixingcited by 1
  2. 2023A Comprehensive Empirical Evaluation of Existing Word Embedding Approachescited by 1
  3. 2023Towards Fair and Explainable AI using a Human-Centered AI Approachcited by 1
  4. 2023Linguistically-Informed Neural Architectures for Lexical, Syntactic and Semantic Tasks in Sanskritcited by 1
  5. 2021Evaluation of Morphological Embeddings for the Russian Languagecited by 0
  6. 2021Evaluation of Morphological Embeddings for English and Russian Languagescited by 0
  7. 2021Ground Truths for the Humanitiescited by 0
  8. 2021Evaluating Word Embeddings with Categorical Modularitycited by 0
  9. 2022An Evaluation Dataset for Legal Word Embedding: A Case Study On Chinese Codexcited by 0
  10. 2023Bridging Natural Language Processing and Psycholinguistics: computationally grounded semantic similarity datasets for Basque and Spanishcited by 0
  11. 2023Assessing Linguistic Generalisation in Language Models: A Dataset for Brazilian Portuguesecited by 0
  12. 2025An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasetscited by 0
  13. 2025Intrinsic vs. Extrinsic Evaluation of Czech Sentence Embeddings: Semantic Relevance Doesn't Help with MT Evaluationcited by 0
  14. 2025BlueGlass: A Framework for Composite AI Safetycited by 0