TREC-DL
Emerging7papers using it
2024first seen
The 'TREC DL' dataset/benchmark contains a collection of documents and queries used to evaluate the effectiveness of text reranking models in information retrieval systems.
Papers using TREC-DL (7)
- ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text RerankingPrecise Zero-Shot Pointwise Ranking with LLMs through Post-Aggregated Global Context InformationAcuRank: Uncertainty-Aware Adaptive Computation for Listwise RerankingPseudo Relevance Feedback is Enough to Close the Gap Between Small and Large Dense Retrieval ModelsRankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language ModelsScaling Sparse and Dense Retrieval in Decoder-Only LLMsFew-shot Prompting for Pairwise Ranking: An Effective Non-Parametric
Retrieval Model