Search Results for author:
Found 3 papers, 1 papers with code
Improving Conversational Recommendation Systems’ Quality with Context-Aware Item Meta-Information
In this paper, we propose a simple yet effective architecture comprising a pre-trained language model (PLM) and an item metadata encoder to integrate the recommendation and the dialog generation better.
Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Information
The encoder learns to map item metadata to embeddings that can reflect the semantic information in the dialog context.
AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All
A commonly observed problem of the state-of-the-art natural language technologies, such as Amazon Alexa and Apple Siri, is that their services do not extend to most developing countries' citizens due to language barriers.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
