Agreement-based clustering of annotators improves performance on subjective NLP tasks by capturing diverse perspectives better than majority voting or per-annotator modeling.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A workshop proposal to reflect on HCI's core identity and the importance of human elements in the era of generative AI.
citing papers explorer
-
Beyond Majority Voting: Agreement-Based Clustering to Model Annotator Perspectives in Subjective NLP Tasks
Agreement-based clustering of annotators improves performance on subjective NLP tasks by capturing diverse perspectives better than majority voting or per-annotator modeling.
-
What is (H)CI: Why Does the "Human'' Matter?
A workshop proposal to reflect on HCI's core identity and the importance of human elements in the era of generative AI.