When Labels Lie: Making Machine Learning Smarter with Annotator Metadata
Supervised machine learning is only as good as the data itβs trained on. But hereβs the catch: when we rely on crowdsourced annotators toβ¦
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:
11.10.2025 13:01 β
π 2
π 1
π¬ 0
π 0
Thank you for letting me in!!
30.09.2023 03:05 β
π 1
π 0
π¬ 0
π 0
Lynnette H. X. Ng
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 π
29.09.2023 15:45 β
π 0
π 0
π¬ 0
π 0
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
29.09.2023 14:37 β
π 9
π 1
π¬ 1
π 0