activity
20182021
most citedConsolidating Commonsense Knowledge

9 citations · 19 across the 6 of their papers we have counts for

collaborators

10 papers

cs.AI20211 cited

Analyzing Race and Country of Citizenship Bias in Wikidata

Zaina Shaik, Filip Ilievski, Fred Morstatter

As an open and collaborative knowledge graph created by users and bots, it is possible that the knowledge in Wikidata is biased in regards to multiple factors such as gender, race,…

cs.AI2021

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…

cs.CL2021

Do Language Models Perform Generalizable Commonsense Inference?

Peifeng Wang, Filip Ilievski, Muhao Chen +1

Inspired by evidence that pretrained language models (LMs) encode commonsense knowledge, recent work has applied LMs to automatically populate commonsense knowledge graphs (CKGs).…

cs.CL2021

Representing Numbers in NLP: a Survey and a Vision

Avijit Thawani, Jay Pujara, Pedro A. Szekely +1

NLP systems rarely give special consideration to numbers found in text. This starkly contrasts with the consensus in neuroscience that, in the brain, numbers are represented differ…

cs.AI2021

Dimensions of Commonsense Knowledge

Filip Ilievski, Alessandro Oltramari, Kaixin Ma +3

Commonsense knowledge is essential for many AI applications, including those in natural language processing, visual processing, and planning. Consequently, many sources that includ…

cs.CL20209 cited

Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question Answering

Kaixin Ma, Filip Ilievski, Jonathan Francis +3

Recent developments in pre-trained neural language modeling have led to leaps in accuracy on commonsense question-answering benchmarks. However, there is increasing concern that mo…