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Found 8 papers, 3 papers with code
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
In addition, to demonstrate extensi-bility to additional reasoning types we evaluate on multi-hopreasoning datasets and a new Temporal KBQA benchmarkdataset on Wikidata, namedTempQA-WD1, introduced in thispaper.
Knowledge Graph Question Answering via SPARQL Silhouette Generation
Experimental results show that the quality of generated SPARQL silhouette in the first stage is outstanding for the ideal scenarios but for realistic scenarios (i. e. noisy linker), the quality of the resulting SPARQL silhouette drops drastically.
Explanations for CommonsenseQA: New Dataset and Models
We human-annotate a first-of-its-kind dataset (called ECQA) of positive and negative properties, as well as free-flow explanations, for $11K$ QA pairs taken from the CQA dataset.
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Knowledge base question answering (KBQA)is an important task in Natural Language Processing.
Inductive Quantum Embedding
Our training runs 9-times faster than the original QE scheme on this task.
The TechQA Dataset
We introduce TechQA, a domain-adaptation question answering dataset for the technical support domain.
A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation
Designing such a network, as well as collecting jointly labeled data for training is a non-trivial task.
Max-Margin Feature Selection
In this paper, we formulate the task of feature selection as a one class SVM problem in a space where features correspond to the data points and instances correspond to the dimensions.