Papers by Yuval Merhav

3 papers
Design Challenges in Named Entity Transliteration (C18-1)

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Challenge: Named entity transliteration is an important component in many search and language understanding tasks.
Approach: They empirically evaluate a named entity transliteration task using traditional methods . they use a stack of convolutional layers to create a neural network with a new approach .
Outcome: The proposed system outperforms two neural approaches in the named entity transliteration task.
Towards Realistic Single-Task Continuous Learning Research for NER (2021.findings-emnlp)

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Challenge: Academic datasets are often static and contain data that is annotated all at once based on fixed annotation guidelines.
Approach: They propose to build a single-task continuous learning dataset from an existing dataset and release it along with the code to the research community.
Outcome: The proposed model is based on an existing dataset and released to the research community.
Controlled Data Generation via Insertion Operations for NLU (2022.naacl-industry)

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Challenge: a new approach to annotate live traffic is emerging to be cost-effective and efficient . manual data annotation is expensive and not preferred for meeting customer privacy expectations .
Approach: They propose a targeted synthetic data generation technique by inserting tokens into a given semantic signature.
Outcome: The proposed approach achieves the same accuracy as training with all available data on a voice assistant dataset.

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