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Found 5 papers, 1 papers with code
Graph-to-Text Generation with Dynamic Structure Pruning
Most graph-to-text works are built on the encoder-decoder framework with cross-attention mechanism.
Learning Explicit User Interest Boundary for Recommendation
The core objective of modelling recommender systems from implicit feedback is to maximize the positive sample score $s_p$ and minimize the negative sample score $s_n$, which can usually be summarized into two paradigms: the pointwise and the pairwise.
Improving Encoder by Auxiliary Supervision Tasks for Table-to-Text Generation
However, it is hard for a vanilla encoder to capture these.
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Table-to-Text Generation
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Learning Better Representation for Tables by Self-Supervised Tasks
Secondly, the target texts in training dataset may contain redundant information or facts do not exist in the input tables.
FC2RN: A Fully Convolutional Corner Refinement Network for Accurate Multi-Oriented Scene Text Detection
Accurate detection of multi-oriented text with large variations of scales, orientations, and aspect ratios is of great significance.
