activity
20212026
most citedPINTO: Faithful Language Reasoning Using Prompt-Generated Rationales

21 citations · 71 across the 31 of their papers we have counts for

collaborators
Showing cs.AIShow all

8 papers · 1 filter

cs.AI2024

SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense

Yifan Jiang, Filip Ilievski, Kaixin Ma

While vertical thinking relies on logical and commonsense reasoning, lateral thinking requires systems to defy commonsense associations and overwrite them through unconventional th…

cs.AI2023★ 2 cited

Case-Based Reasoning with Language Models for Classification of Logical Fallacies

Zhivar Sourati, Filip Ilievski, Hông-Ân Sandlin +1

The ease and speed of spreading misinformation and propaganda on the Web motivate the need to develop trustworthy technology for detecting fallacies in natural language arguments.…

cs.AI2022★ 5 cited

Multimodal and Explainable Internet Meme Classification

Abhinav Kumar Thakur, Filip Ilievski, Hông-Ân Sandlin +4

In the current context where online platforms have been effectively weaponized in a variety of geo-political events and social issues, Internet memes make fair content moderation a…

cs.AI2022

Does Wikidata Support Analogical Reasoning?

Filip Ilievski, Jay Pujara, Kartik Shenoy

Analogical reasoning methods have been built over various resources, including commonsense knowledge bases, lexical resources, language models, or their combination. While the wide…

cs.AI2022

Enriching Wikidata with Linked Open Data

Bohui Zhang, Filip Ilievski, Pedro Szekely

Large public knowledge graphs, like Wikidata, contain billions of statements about tens of millions of entities, thus inspiring various use cases to exploit such knowledge graphs.…

cs.AI2022★ 4 cited

Understanding Narratives through Dimensions of Analogy

Thiloshon Nagarajah, Filip Ilievski, Jay Pujara

Analogical reasoning is a powerful qualitative reasoning tool that enables humans to connect two situations, and to generalize their knowledge from familiar to novel situations. Co…

cs.AI2022★ 3 cited

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…

cs.AI2021★ 6 cited

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…