Type prediction
41 papers with code • 3 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Type prediction
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Libraries
Use these libraries to find Type prediction models and implementations
ManyTypes4TypeScript
Latest papers with no code
Win-Win Cooperation: Bundling Sequence and Span Models for Named Entity Recognition
Previous research has demonstrated that the two paradigms have clear complementary advantages, but few models have attempted to leverage these advantages in a single NER model as far as we know.
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Scarcity of labeled histopathology data limits the applicability of deep learning methods to under-profiled cancer types and labels.
Scalable privacy-preserving cancer type prediction with homomorphic encryption
Privacy concerns in outsourced ML, especially in the field of genetics, motivate the use of encrypted computation, like Homomorphic Encryption (HE).
Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition
Recent years have witnessed the improving performance of Chinese Named Entity Recognition (NER) from proposing new frameworks or incorporating word lexicons.
Automatic Identification and Classification of Bragging in Social Media
Bragging is a speech act employed with the goal of constructing a favorable self-image through positive statements about oneself.
CORE: A Knowledge Graph Entity Type Prediction Method via Complex Space Regression and Embedding
A new KG entity type prediction method, named CORE (COmplex space Regression and Embedding), is proposed in this work.
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training
Representation learning models for Knowledge Graphs (KG) have proven to be effective in encoding structural information and performing reasoning over KGs.
Semantic Answer Type and Relation Prediction Task (SMART 2021)
The Semantic Answer Type and Relation Prediction Task (SMART) task is one of the ISWC 2021 Semantic Web challenges.
Multilingual training for Software Engineering
As a way around such data bottlenecks, we present evidence suggesting that human-written code in different languages (which performs the same function), is rather similar, and particularly preserving of identifier naming patterns; we further present evidence suggesting that identifiers are a very important element of training data for software engineering tasks.
Semantic Answer Type Prediction using BERT: IAI at the ISWC SMART Task 2020
This paper summarizes our participation in the SMART Task of the ISWC 2020 Challenge.
