mlsanityData to 14 Oct 2026

Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings

arXiv 2205.13858 ↗First posted 27 May 2022cs.CLcited by 18

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Abstract (arXiv)

Word embeddings have advanced the state of the art in NLP across numerous tasks. Understanding the contents of dense neural representations is of utmost interest to the computational semantics community. We propose to focus on relating these opaque word vectors with human-readable definitions, as found in dictionaries. This problem naturally divides into two subtasks: converting definitions into embeddings, and converting embeddings into definitions. This task was conducted in a multilingual setting, using comparable sets of embeddings trained homogeneously.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 26 of its 66 references that are in the map. First posted on arXiv 27 May 2022.

Builds on

26 of 66 references.

References · 26

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2020Language Models are Few-Shot Learnerscited by 32,419
  4. 2022Generative Adversarial Networkscited by 5,627
  5. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  6. 2019How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddingscited by 784
  7. 2019MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distancecited by 418
  8. 2013One Billion Word Benchmark for Measuring Progress in Statistical Language Modelingcited by 308
  9. 2021All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Qualitycited by 156
  10. 2019Distributional Semantics and Linguistic Theorycited by 53
  11. 2020Pre-Training Transformers as Energy-Based Cloze Modelscited by 52
  12. 2016Definition Modeling: Learning to define word embeddings in natural languagecited by 46
14 more
  1. 2018Conditional Generators of Words Definitionscited by 35
  2. 2015Learning to Understand Phrases by Embedding the Dictionarycited by 33
  3. 2019Meaning to Form: Measuring Systematicity as Informationcited by 16
  4. 2019Multi-channel Reverse Dictionary Modelcited by 16
  5. 2019Mark my Word: A Sequence-to-Sequence Approach to Definition Modelingcited by 15
  6. 2019Incorporating Sememes into Chinese Definition Modelingcited by 13
  7. 2020BERT for Monolingual and Cross-Lingual Reverse Dictionarycited by 12
  8. 2016Implementing a Reverse Dictionary, based on word definitions, using a Node-Graph Architecturecited by 8
  9. 2019Improving Interpretability of Word Embeddings by Generating Definition and Usagecited by 5
  10. 2020Evaluating a Multi-sense Definition Generation Model for Multiple Languagescited by 5
  11. 2020Learning Architectures from an Extended Search Space for Language Modelingcited by 4
  12. 2022BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modelingcited by 3
  13. 2021PREDICT: Persian Reverse Dictionarycited by 2
  14. 2022IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representationscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 6; 2024: 10; 2025: 0; 2026: 1.

18 papers.

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  1. 2024Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformerscited by 44
  2. 2024SemEval-2024 Shared Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakescited by 24
  3. 2023Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysiscited by 19
  4. 2024Definition generation for lexical semantic change detectioncited by 7
  5. 2023Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitionscited by 4
  6. 2023"Definition Modeling: To model definitions." Generating Definitions With Little to No Semanticscited by 4
  7. 2024Isotropy, Clusters, and Classifierscited by 4
  8. 2023LlaMaVAE: Guiding Large Language Model Generation via Continuous Latent Sentence Spacescited by 3
  9. 2024CoLLEGe: Concept Embedding Generation for Large Language Modelscited by 3
  10. 2024Presence or Absence: Are Unknown Word Usages in Dictionaries?cited by 3
  11. 2024AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modelingcited by 3
  12. 2024DORE: A Dataset For Portuguese Definition Generationcited by 2
6 more
  1. 20233D-EX : A Unified Dataset of Definitions and Dictionary Examplescited by 1
  2. 2024Enriching Word Usage Graphs with Cluster Definitionscited by 1
  3. 20221Cademy at Semeval-2022 Task 1: Investigating the Effectiveness of Multilingual, Multitask, and Language-Agnostic Tricks for the Reverse Dictionary Taskcited by 0
  4. 2023WIKITIDE: A Wikipedia-Based Timestamped Definition Pairs Datasetcited by 0
  5. 2024Deep-change at AXOLOTL-24: Orchestrating WSD and WSI Models for Semantic Change Modelingcited by 0
  6. 2026MURAD: A Large-Scale Multi-Domain Unified Reverse Arabic Dictionary Datasetcited by 0