Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval (2104.05883v1)
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.
- Chen Zhao (249 papers)
- Chenyan Xiong (95 papers)
- Jordan Boyd-Graber (68 papers)
- Hal Daumé III (76 papers)