Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Model

Instruction-tuned language models (LM) are able to respond to imperative commands, providing a more natural user interface compared to their base counterparts. In this work, we present Promptriever, the first retrieval model able to be prompted like an LM. To train Promptriever, we curate and release a new instance-level instruction training set from MS MARCO, spanning nearly 500k instances. Promptriever not only achieves strong performance on standard retrieval tasks, but also follows instructions. We observe: (1) large gains (reaching SoTA) on following detailed relevance instructions (+14.3

Research goal: Can adversarial training on multi-hop queries from MuSiQue improve retriever robustness on out-of-domain BEIR subsets (e.g., SciFact, TREC-COVID) compared to single-context adversarial training, measured by MRR@10?

Autonomous synthesis report generated by SOVEREIGN Research Kernel. Tribunal consensus score: 7.5/10.