mlsanityData to 14 Oct 2026

BERT(s) to Detect Multiword Expressions

arXiv 2208.07832 ↗First posted 16 Aug 2022cs.CLcited by 5

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Abstract (arXiv)

Multiword expressions (MWEs) present groups of words in which the meaning of the whole is not derived from the meaning of its parts. The task of processing MWEs is crucial in many natural language processing (NLP) applications, including machine translation and terminology extraction. Therefore, detecting MWEs is a popular research theme. In this paper, we explore state-of-the-art neural transformers in the task of detecting MWEs.We empirically evaluate several transformer models in the dataset for SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM). We show that transformer models outperform the previous neural models based on long short-term memory (LSTM). The code and pre-trained model will be made freely available to the community.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 16 Aug 2022.

Builds on

13 of 33 references.

References · 13

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  4. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
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  6. 2015Bidirectional LSTM-CRF Models for Sequence Taggingcited by 546
  7. 2021FBERT: A Neural Transformer for Identifying Offensive Contentcited by 30
  8. 2021An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformerscited by 18
  9. 2021Comparing Approaches to Dravidian Language Identificationcited by 11
  10. 2019Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressionscited by 5
  11. 2022DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domaincited by 4
  12. 2021WLV-RIT at GermEval 2021: Multitask Learning with Transformers to Detect Toxic, Engaging, and Fact-Claiming Commentscited by 3
1 more
  1. 2019Concept Discovery through Information Extraction in Restaurant Domaincited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 0; 2026: 2.

5 papers.

  1. 2023DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskritcited by 1
  2. 2026From Lemmas to Dependencies: What Signals Drive Light Verbs Classification?cited by 1
  3. 2022Transformer-based Detection of Multiword Expressions in Flower and Plant Namescited by 0
  4. 2023Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plantscited by 0
  5. 2026Supervision versus Demonstration-Based In-Context Learning for Multiword Expression Classificationcited by 0