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May 11, 2020 · To facilitate the training of neural network models, researchers created large datasets of paired utterances and their meaning representations.
In this paper, we present the novel task of Schema-Guided Natural Language Generation (SG-NLG). Here, the goal is still to generate a natural language prompt.
This SG-NLG dataset is designed to make it easier to conduct NLG experiments on the SGD data. We pre-process SGD by pairing the schema for each system turn with ...
In this work, we focus on stylistic control and evaluation for schema-guided NLG, with joint goals of achieving both semantic and stylistic control. We ...
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In this paper, we present the novel task of Schema-Guided Natural Language Generation (SG-NLG). Here, the goal is still to generate a natural language ...
The SG-NLG dataset is a pre-processed version of the DSTC8 Schema-Guided Dialogue SGD dataset, designed specifically for data-to-text NLG.
The SG-NLG dataset is a pre-processed version of the DSTC8 Schema-Guided Dialogue SGD dataset, designed specifically for data-to-text Natural Language ...
The goal of the task is to generate a natural language string to realize an input meaning representation, hence large datasets of paired utterances and their ...
Oct 24, 2022 · First, we propose a schema-guided approach which conditions the generation on a schema describing the API in natural language. Our second ...
Natural Language Generation (NLG) for task-oriented dialogue systems focuses on communicating specific content accurately, fluently, and coherently.