Papers by Ionut-Catalin Sandu
Large Sequence Representation Learning via Multi-Stage Latent Transformers (2022.coling-1)
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| Challenge: | a novel algorithm for named-entity recognition (NER) uses language and spatial features to predict entity tags for structured text . a dataset of 11,926 images depicting food product labels is used to perform NER tasks . |
| Approach: | They propose a multi-stage transformer architecture for named-entity recognition . they propose RADAR, an LSTM classifier operating at character level, to refine NER predictions . |
| Outcome: | The proposed method outperforms two competing models on a food label dataset. |