lynnette

When Labels Lie: Making Machine Learning Smarter with Annotator Metadata Supervised machine learning is only as good as the data it’s trained on. But here’s the catch: when we rely on crowdsourced annotators to…

Crowdsourced labels often hide bias, fatigue & noise. This #CSCW2025 paper by @quarbby.bsky.social, @feedkoko.bsky.social et. al shows how annotator metadata (speed, agreement, effort) can boost ML models of users' deception & disclosure. More:

Yay I got added!

Can I be added? 😀

Please add me!

Thank you for letting me in!!

Hello! I'm a PhD student at #carnegiemellonuniversity doing #societalcomputing! Specifically looking at the human communication and automation! My work can be found on my website at quarbby.github.io 😀

Hello! I'm a PhD student at #carnegiemellonuniversity doing #societalcomputing! Specifically looking at the human communication and automated methods! Looking forward to interacting with #PhDSky and ##HiSciSky