2 citations · 5 across the 5 of their papers we have counts for
5 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…
Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps
Arman Noroozian, Lorena Aldana, Marta Arisi +21
The rapid advancement of Generative AI (GenAI) relies heavily on the digital commons, a vast collection of free and open online content that is created, shared, and maintained by c…
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…
Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions
Aidan Hogan, Xin Luna Dong, Denny Vrandečić +1
Much has been discussed about how Large Language Models, Knowledge Graphs and Search Engines can be combined in a synergistic manner. A dimension largely absent from current academ…
Architecture for a multilingual Wikipedia
Denny Vrandečić
Wikipedia's vision is a world in which everyone can share in the sum of all knowledge. In its first two decades, this vision has been very unevenly achieved. One of the largest hin…