30 citations · 66 across the 10 of their papers we have counts for
14 papers
Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning
Fei Wang, Zhewei Xu, Pedro Szekely +1
Controlled table-to-text generation seeks to generate natural language descriptions for highlighted subparts of a table. Previous SOTA systems still employ a sequence-to-sequence g…
Augmenting Knowledge Graphs for Better Link Prediction
Jiang Wang, Filip Ilievski, Pedro Szekely +1
Embedding methods have demonstrated robust performance on the task of link prediction in knowledge graphs, by mostly encoding entity relationships. Recent methods propose to enhanc…
Evaluating Machine Common Sense via Cloze Testing
Ehsan Qasemi, Lee Kezar, Jay Pujara +1
Language models (LMs) show state of the art performance for common sense (CS) question answering, but whether this ability implies a human-level mastery of CS remains an open quest…
Table-based Fact Verification with Salience-aware Learning
Fei Wang, Kexuan Sun, Jay Pujara +2
Tables provide valuable knowledge that can be used to verify textual statements. While a number of works have considered table-based fact verification, direct alignments of tabular…
Creating and Querying Personalized Versions of Wikidata on a Laptop
Hans Chalupsky, Pedro Szekely, Filip Ilievski +2
Application developers today have three choices for exploiting the knowledge present in Wikidata: they can download the Wikidata dumps in JSON or RDF format, they can use the Wikid…
User-friendly Comparison of Similarity Algorithms on Wikidata
Filip Ilievski, Pedro Szekely, Gleb Satyukov +1
While the similarity between two concept words has been evaluated and studied for decades, much less attention has been devoted to algorithms that can compute the similarity of nod…