Biomedical Information Retrieval
7 papers with code • 3 benchmarks • 5 datasets
To address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval.
We propose this method for its added value relative to existing graph analytical methodology, and in the real world context of biomedical knowledge discovery applicability.
Speculation is a naturally occurring phenomena in textual data, forming an integral component of many systems, especially in the biomedical information retrieval domain.
This has made distilled and dense models, due to latency constraints, the go-to choice for deployment in real-world retrieval applications.
BioCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval
Experimental results show that BioCPT sets new state-of-the-art performance on five biomedical IR tasks, outperforming various baselines including much larger models such as GPT-3-sized cpt-text-XL.