Papers by Kadri Hacioglu

2 papers
SpeechLLMs for Large-scale Contextualized Zero-shot Slot Filling (2025.emnlp-industry)

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Challenge: Slot filling is a key subtask in spoken language understanding (SLU) . recent advent of speech-based large language models has opened new avenues for speech understanding .
Approach: They propose to improve slot-filling task by creating an empirical upper bound for the task . they propose to use a speech-based large language model to integrate speech and text modalities .
Outcome: The proposed model improves slot filling performance while reducing generalization gaps.
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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