mlsanityData to 14 Oct 2026

WordAlchemy: A transformer-based Reverse Dictionary

arXiv 2204.10181 ↗First posted 16 Apr 2022cs.CL cs.AIcited by 3

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Abstract (arXiv)

A reverse dictionary takes a target word's description as input and returns the words that fit the description. Reverse Dictionaries are useful for new language learners, anomia patients, and for solving common tip-of-the-tongue problems (lethologica). Currently, there does not exist any Reverse Dictionary provider with support for any Indian Language. We present a novel open-source cross-lingual reverse dictionary system with support for Indian languages. In this paper, we propose a transformer-based deep learning approach to tackle the limitations faced by the existing systems using the mT5 model. This architecture uses the Translation Language Modeling (TLM) technique, rather than the conventional BERT's Masked Language Modeling (MLM) technique.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 7 of its 17 references that are in the map. First posted on arXiv 16 Apr 2022.

Builds on

7 of 17 references.

References · 7

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  3. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  4. 2015Learning to Understand Phrases by Embedding the Dictionarycited by 33
  5. 2019Multi-channel Reverse Dictionary Modelcited by 16
  6. 2020BERT for Monolingual and Cross-Lingual Reverse Dictionarycited by 12
  7. 2016Implementing a Reverse Dictionary, based on word definitions, using a Node-Graph Architecturecited by 8

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3 papers.