Papers by Maria Minakova
Entity Contrastive Learning in a Large-Scale Virtual Assistant System (2023.acl-industry)
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| Challenge: | Named Entity Recognition (NER) tasks are a well-studied and fundamental task within Natural Language Understanding (NLU). |
| Approach: | They propose to incorporate entity contrastive learning into a virtual assistant system to improve NER models by clustering similar inputs closer together in a learned representation space. |
| Outcome: | The proposed model improves against a production baseline system that does not use contrastive learning. |
Influence Scores at Scale for Efficient Language Data Sampling (2023.emnlp-main)
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| Challenge: | Recent studies have shown that ML models can be fine-tuned on as much data as possible without degradation in performance metrics. |
| Approach: | They evaluate the applicability of influence scores in language classification tasks by random sampling and stress-testing one of the scores. |
| Outcome: | The proposed model can be fine-tuned on 50% of the original data without degradation in performance metrics. |