Command Palette
Search for a command to run...
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Abstract
We propose a simple and efficient multi-hop dense retrieval approach for answering complex open-domain questions, which achieves state-of-the-art performance on two multi-hop datasets, HotpotQA and multi-evidence FEVER. Contrary to previous work, our method does not require access to any corpus-specific information, such as inter-document hyperlinks or human-annotated entity markers, and can be applied to any unstructured text corpus. Our system also yields a much better efficiency-accuracy trade-off, matching the best published accuracy on HotpotQA while being 10 times faster at inference time.
Code Repositories
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| question-answering-on-hotpotqa | Recursive Dense Retriever | ANS-EM: 0.623 ANS-F1: 0.753 JOINT-EM: 0.418 JOINT-F1: 0.666 SUP-EM: 0.575 SUP-F1: 0.809 |
Build AI with AI
From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.