most citedA Study of Situational Reasoning for Traffic Understanding

8 citations · 21 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2023

BRAINTEASER: Lateral Thinking Puzzles for Large Language Models

Yifan Jiang, Filip Ilievski, Kaixin Ma +1

The success of language models has inspired the NLP community to attend to tasks that require implicit and complex reasoning, relying on human-like commonsense mechanisms. While su…

cs.CL20238 cited

A Study of Situational Reasoning for Traffic Understanding

Jiarui Zhang, Filip Ilievski, Kaixin Ma +3

Intelligent Traffic Monitoring (ITMo) technologies hold the potential for improving road safety/security and for enabling smart city infrastructure. Understanding traffic situation…

cs.CV20231 cited

Using Visual Cropping to Enhance Fine-Detail Question Answering of BLIP-Family Models

Jiarui Zhang, Mahyar Khayatkhoei, Prateek Chhikara +1

Visual Question Answering is a challenging task, as it requires seamless interaction between perceptual, linguistic, and background knowledge systems. While the recent progress of…

cs.CL20231 cited

A Study of Slang Representation Methods

Aravinda Kolla, Filip Ilievski, Hông-Ân Sandlin +1

Considering the large amount of content created online by the minute, slang-aware automatic tools are critically needed to promote social good, and assist policymakers and moderato…

cs.CL20227 cited

Coalescing Global and Local Information for Procedural Text Understanding

Kaixin Ma, Filip Ilievski, Jonathan Francis +2

Procedural text understanding is a challenging language reasoning task that requires models to track entity states across the development of a narrative. A complete procedural unde…

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.…