Papers › Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval

Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval

13 Apr 2021NAACL 2021 4arXiv:2104.05883archive 2025-07-28

Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III

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.

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