Нейрондық Ранжировщиктер
method
ID: neuralrankers
Related Papers
Contrastive Fine-tuning Improves Robustness for Neural Rankers
The performance of state-of-the-art neural rankers can deteriorate substantially when ex- posed to noisy inputs or applied to a new domain. In this paper, we present a novel method for …...
Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval
AbstractState-of-the-art neural (re)rankers are notoriously data-hungry which – given the lack of large-scale training data in languages other than English – makes them rarely used in multilingual and cross-lingual retrieval …...