StratRAG is a new benchmark dataset for multi-hop retrieval in RAG systems with noisy document pools, where hybrid retrieval reaches Recall@2 of 0.70 but bridge questions remain harder at 0.67.
Hybrid listwise optimization for retrieval models
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.IR 2years
2026 2representative citing papers
A hybrid supervision method for bi-encoder retrievers combines graded relevance from teacher models, production retrieval priors, and selective engagement to improve relevance and NDCG over Walmart's current sponsored search system.
citing papers explorer
-
StratRAG: A Multi-Hop Retrieval Evaluation Dataset for Retrieval-Augmented Generation Systems
StratRAG is a new benchmark dataset for multi-hop retrieval in RAG systems with noisy document pools, where hybrid retrieval reaches Recall@2 of 0.70 but bridge questions remain harder at 0.67.
-
Unified Supervision for Walmart's Sponsored Search Retrieval via Joint Semantic Relevance and Behavioral Engagement Modeling
A hybrid supervision method for bi-encoder retrievers combines graded relevance from teacher models, production retrieval priors, and selective engagement to improve relevance and NDCG over Walmart's current sponsored search system.