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Found 7 papers, 5 papers with code
A Usage-centric Take on Intent Understanding in E-Commerce
Identifying and understanding user intents is a pivotal task for E-Commerce.
Task-specific Pre-training and Prompt Decomposition for Knowledge Graph Population with Language Models
Our system is the winner of track 1 of the LM-KBC challenge, based on BERT LM; it achieves 55. 0% F-1 score on the hidden test set of the challenge.
Learning to Generate Wikipedia Summaries for Underserved Languages from Wikidata
While Wikipedia exists in 287 languages, its content is unevenly distributed among them.
Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples
We explore the problem of generating natural language summaries for Semantic Web data.
A Neural Network Approach for Knowledge-Driven Response Generation
Our model is based on a Recurrent Neural Network (RNN) that is trained over concatenated sequences of comments, a Convolution Neural Network that is trained over Wikipedia sentences and a formulation that couples the two trained embeddings in a multimodal space.
