4 papers
To Believe or Not To Believe: Comparing Supporting Information Tools to Aid Human Judgments of AI Veracity
Jessica Irons, Patrick Cooper, Necva Bolucu +6
With increasing awareness of the hallucination risks of generative artificial intelligence (AI), we see a growing shift toward providing information tooling to help users determine…
MetaLead: A Comprehensive Human-Curated Leaderboard Dataset for Transparent Reporting of Machine Learning Experiments
Roelien C. Timmer, Necva Bölücü, Stephen Wan
Leaderboards are crucial in the machine learning (ML) domain for benchmarking and tracking progress. However, creating leaderboards traditionally demands significant manual effort.…
A Position Paper on the Automatic Generation of Machine Learning Leaderboards
Roelien C Timmer, Yufang Hou, Stephen Wan
An important task in machine learning (ML) research is comparing prior work, which is often performed via ML leaderboards: a tabular overview of experiments with comparable conditi…
Honeyfile Camouflage: Hiding Fake Files in Plain Sight
Roelien C. Timmer, David Liebowitz, Surya Nepal +1
Honeyfiles are a particularly useful type of honeypot: fake files deployed to detect and infer information from malicious behaviour. This paper considers the challenge of naming ho…