CDVM formulates data pruning as maximizing total data influence while constraining excessive contributions to any single test point, yielding robust performance on the OpenDataVal benchmark in low-data regimes.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Constraint-Data-Value-Maximization: Utilizing Data Attribution for Effective Data Pruning in Low-Data Environments
CDVM formulates data pruning as maximizing total data influence while constraining excessive contributions to any single test point, yielding robust performance on the OpenDataVal benchmark in low-data regimes.