ZhenwenZhang/Slot_Filling
Latest research advances on semantic slot filling.
This is a collection of research papers and model performance benchmarks focused on 'slot filling', a technique used to extract specific pieces of information from spoken or written phrases. It provides a historical overview of different models and their accuracy in identifying key data points within user requests, such as flight destinations or times. This resource is for researchers or engineers working on natural language understanding in conversational AI systems.
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Use this if you are an academic researcher or an AI/ML engineer needing to understand the state-of-the-art and historical performance of models for extracting specific entities from user utterances.
Not ideal if you are looking for a ready-to-use tool or code for implementing a slot filling system, as this repository primarily serves as a literature review.
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Feb 13, 2023
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