@misc{zhao2021multi-step,
author = {Zhao, Chen and Xiong, Chenyan and Boyd-Graber, Jordan L. and Daumé III, Hal},
title = {Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval},
howpublished = {arXiv},
year = {2021},
month = {April},
abstract = {Complex question answering often requires finding a reasoning chain that consists of multiple evidence pieces. Current approaches incorporate the strengths of structured knowledge and unstructured text, assuming text corpora is semi-structured. Building on dense retrieval methods, we propose a new multi-step retrieval approach (BeamDR) that iteratively forms an evidence chain through beam search in dense representations. When evaluated on multi-hop question answering, BeamDR is competitive to state-of-the-art systems, without using any semi-structured information. Through query composition in dense space, BeamDR captures the implicit relationships between evidence in the reasoning chain. The code is available at https://github.com/ henryzhao5852/BeamDR.},
url = {http://approjects.co.za/?big=en-us/research/publication/multi-step-reasoning-over-unstructured-text-with-beam-dense-retrieval/},
}