Introduces the Annotation Scarcity Paradox to describe how model scaling in low-resource NLP outpaces the human expertise required for authentic evaluation, threatening the validity of reported progress.
Bottom-up data trusts: Disturbing the ‘one size fits all’approach to data governance
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
The Annotation Scarcity Paradox in Low-Resource NLP Evaluation: A Decade of Acceleration and Emerging Constraints
Introduces the Annotation Scarcity Paradox to describe how model scaling in low-resource NLP outpaces the human expertise required for authentic evaluation, threatening the validity of reported progress.