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Found 7 papers, 3 papers with code
TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search
Text encoders based on C-DSSM or transformers have demonstrated strong performance in many Natural Language Processing (NLP) tasks.
SemEval-2020 Task 5: Counterfactual Recognition
Subtask-1 aims to determine whether a given sentence is a counterfactual statement or not.
Graph Convolution for Multimodal Information Extraction from Visually Rich Documents
In VRDs, visual and layout information is critical for document understanding, and texts in such documents cannot be serialized into the one-dimensional sequence without losing information.
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding
Entity recognition is a widely benchmarked task in natural language processing due to its massive applications.
Recommending Complementary Products in E-Commerce Push Notifications with a Mixture Model Approach
The item with the highest predicted open rate is then chosen to be included in the push notification message for each user.
SAME but Different: Fast and High-Quality Gibbs Parameter Estimation
SAME (State Augmentation for Marginal Estimation) \cite{Doucet99, Doucet02} is an approach to MAP parameter estimation which gives improved parameter estimates over direct Gibbs sampling.
Sparse Allreduce: Efficient Scalable Communication for Power-Law Data
Many large datasets exhibit power-law statistics: The web graph, social networks, text data, click through data etc.
