Active learning applied to noisy LLM pairwise judgments improves NDCG@10 per call in budget-constrained reranking and enables unbiased aggregation via a randomized-direction single-call oracle.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Active Learners as Efficient PRP Rerankers
Active learning applied to noisy LLM pairwise judgments improves NDCG@10 per call in budget-constrained reranking and enables unbiased aggregation via a randomized-direction single-call oracle.