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Found 5 papers, 3 papers with code
Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model
Specifically, during neural network training, we naturally model the noise samples in each batch following a hypergeometric distribution parameterized by the noise-rate.
Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models
This paper studies how to automatically generate a natural language text that describes the facts in knowledge graph (KG).
Knowledge-based Review Generation by Coherence Enhanced Text Planning
For global coherence, we design a hierarchical self-attentive architecture with both subgraph- and node-level attention to enhance the correlations between subgraphs.
Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network
First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence.
A Rigorous Study on Named Entity Recognition: Can Fine-tuning Pretrained Model Lead to the Promised Land?
Specifically, we erase name regularity, mention coverage and context diversity respectively from the benchmarks, in order to explore their impact on the generalization ability of models.
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