Apple Workshop on Machine Learning for Health : Web3 and Decentralized AI (DecAI)
AuthorsRamesh Raskar (MIT)
Apple Workshop on Machine Learning for Health : Web3 and Decentralized AI (DecAI)
AuthorsRamesh Raskar (MIT)
Metric-Dependent Annotation Saturation for Learning from Label Distributions
June 23, 2026research area Data Science and Annotation, research area Speech and Natural Language Processing
When annotators disagree on a label, the disagreement itself carries signal—and the number of annotators needed to capture it depends on the evaluation metric. We fine-tune NLI models on label distributions subsampled from ChaosNLI, a dataset providing 100 independent annotator judgments per item, and identify metric-dependent saturation. In our 3-class NLI setting, entropy correlation—whether the model identifies which items elicit…
Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels
June 23, 2026research area Data Science and Annotation, research area Speech and Natural Language Processing
LLM-as-a-judge panels aggregate votes from multiple models, with the expectation that diverse models yield more reliable evaluations. We develop a framework to measure the true informational value of such panels and quantify how far their reliability falls short of the independent-voting ideal. Testing a panel of 9 frontier LLMs from 7 model families on three natural language inference datasets (each with 100 human annotations per item), we find…