kpfriends at SemEval-2022 Task 2: NEAMER -- Named Entity Augmented Multi-word Expression Recognizer
Not on the map. Why?
Abstract (arXiv)
We present NEAMER -- Named Entity Augmented Multi-word Expression Recognizer. This system is inspired by non-compositionality characteristics shared between Named Entity and Idiomatic Expressions. We utilize transfer learning and locality features to enhance idiom classification task. This system is our submission for SemEval Task 2: Multilingual Idiomaticity Detection and Sentence Embedding Subtask A OneShot shared task. We achieve SOTA with F1 0.9395 during post-evaluation phase. We also observe improvement in training stability. Lastly, we experiment with non-compositionality knowledge transfer, cross-lingual fine-tuning and locality features, which we also introduce in this paper.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 22 references that are in the map. First posted on arXiv 17 Apr 2022.
Builds on
7 of 22 references.
References · 7
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2019BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performancecited by 89
- 2020Assessing Phrasal Representation and Composition in Transformerscited by 41
- 2021AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Modelscited by 27
- 2020The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestionscited by 22
Built on by
Citing papers per year: 2022: 1.
1 paper.