Papers by Sindhuja Gopalan

2 papers
Scaling Neural ITN for Numbers and Temporal Expressions in Tamil: Findings for an Agglutinative Low-resource Language (2023.emnlp-industry)

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Challenge: Inverse Text Normalisation (ITN) is a textrewriting task that converts verbalized text to written form.
Approach: They propose to use a seq2seq model, a non-autoregressive text editor and a sequence tagger + rules combination to fine-tune three pre-trained neural models.
Outcome: The proposed model improves with bootstrapping and data augmentation, and bootstrap alone shows a percentage improvement of 14.12 %.
Zero-shot Slot Filling in the Age of LLMs for Dialogue Systems (2025.coling-industry)

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Challenge: Existing methods for zero-shot slot filling focus on text data, overlooking conversational data.
Approach: They propose a method for automatic data annotation with slot induction and black-box knowledge distillation from a teacher LLM to a smaller model.
Outcome: The proposed method outperforms existing models on internal datasets by 26% relative increase in F1 score.

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