69 citations · 205 across the 23 of their papers we have counts for
24 papers
Linear Probing Provides Robust and Efficient Detection of Machine-Generated Text
Gerrit Quaremba, Hanqi Yan, Elizabeth Black +2
Distinguishing machine-generated text (MGT) from human-written text (HWT) becomes increasingly important due to potential misuse. However, most supervised detectors often degrade o…
WETBench: A Benchmark for Detecting Task-Specific Machine-Generated Text on Wikipedia
Gerrit Quaremba, Elizabeth Black, Denny Vrandečić +1
Given Wikipedia's role as a trusted source of high-quality, reliable content, concerns are growing about the proliferation of low-quality machine-generated text (MGT) produced by l…
Using Large Language Models for Knowledge Engineering (LLMKE): A Case Study on Wikidata
Bohui Zhang, Ioannis Reklos, Nitisha Jain +2
In this work, we explore the use of Large Language Models (LLMs) for knowledge engineering tasks in the context of the ISWC 2023 LM-KBC Challenge. For this task, given subject and…
Agreeing and Disagreeing in Collaborative Knowledge Graph Construction: An Analysis of Wikidata
Elisavet Koutsiana, Tushita Yadav, Nitisha Jain +2
In this work, we study disagreements in discussions around Wikidata, an online knowledge community that builds the data backend of Wikipedia. Discussions are essential in collabora…
Multimodal Automated Fact-Checking: A Survey
Mubashara Akhtar, Michael Schlichtkrull, Zhijiang Guo +3
Misinformation is often conveyed in multiple modalities, e.g. a miscaptioned image. Multimodal misinformation is perceived as more credible by humans, and spreads faster than its t…
Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking
Mubashara Akhtar, Oana Cocarascu, Elena Simperl
Evidence data for automated fact-checking (AFC) can be in multiple modalities such as text, tables, images, audio, or video. While there is increasing interest in using images for…