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Found 10 papers, 3 papers with code
Message Passing for Hyper-Relational Knowledge Graphs
We also demonstrate that existing benchmarks for evaluating link prediction (LP) performance on hyper-relational KGs suffer from fundamental flaws and thus develop a new Wikidata-based dataset - WD50K.
Ranked #2 on
Link Prediction
on JF17K
Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs
In this paper, we conduct an empirical investigation of neural query graph ranking approaches for the task of complex question answering over knowledge graphs.
Fair NLP Models with Differentially Private Text Encoders
Encoded text representations often capture sensitive attributes about individuals (e. g., race or gender), which raise privacy concerns and can make downstream models unfair to certain groups.
Formal Ontology Learning from English IS-A Sentences
Ontology learning (OL) is the process of automatically generating an ontological knowledge base from a plain text document.
SimDoc: Topic Sequence Alignment based Document Similarity Framework
Document similarity is the problem of estimating the degree to which a given pair of documents has similar semantic content.
BitSim: An Algebraic Similarity Measure for Description Logics Concepts
In this paper, we propose an algebraic similarity measure {\sigma}BS (BS stands for BitSim) for assigning semantic similarity score to concept definitions in ALCH+ an expressive fragment of Description Logics (DL).
Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years.
An End-to-End Approach for Full Bridging Resolution
We demonstrate the performance of an end-to-end transformer-based higher-order coreference model finetuned for the task of full bridging.
FairGrad: Fairness Aware Gradient Descent
We address the problem of group fairness in classification, where the objective is to learn models that do not unjustly discriminate against subgroups of the population.
Fair Without Leveling Down: A New Intersectional Fairness Definition
In this work, we consider the problem of intersectional group fairness in the classification setting, where the objective is to learn discrimination-free models in the presence of several intersecting sensitive groups.
