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Found 4 papers, 3 papers with code
Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning
Commonsense generation aims to generate a realistic sentence describing a daily scene under the given concepts, which is very challenging, since it requires models to have relational reasoning and compositional generalization capabilities.
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation
Dialog response generation in open domain is an important research topic where the main challenge is to generate relevant and diverse responses.
Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations
We study the problem of coarse-grained response selection in retrieval-based dialogue systems.
ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation
ProphetNet is a pre-training based natural language generation method which shows powerful performance on English text summarization and question generation tasks.
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