RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering
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Cited by 20 in LLM reasoning, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Existing KBQA approaches, despite achieving strong performance on i.i.d. test data, often struggle in generalizing to questions involving unseen KB schema items. Prior ranking-based approaches have shown some success in generalization, but suffer from the coverage issue. We present RnG-KBQA, a Rank-and-Generate approach for KBQA, which remedies the coverage issue with a generation model while preserving a strong generalization capability. Our approach first uses a contrastive ranker to rank a set of candidate logical forms obtained by searching over the knowledge graph. It then introduces a tailored generation model conditioned on the question and the top-ranked candidates to compose the final logical form. We achieve new state-of-the-art results on GrailQA and WebQSP datasets. In particular, our method surpasses the prior state-of-the-art by a large margin on the GrailQA leaderboard. In addition, RnG-KBQA outperforms all prior approaches on the popular WebQSP benchmark, even including the ones that use the oracle entity linking. The experimental results demonstrate the effectiveness of the interplay between ranking and generation, which leads to the superior performance of our proposed approach across all settings with especially strong improvements in zero-shot generalization.
Key facts. Cited by 86 papers in the map (data through 7 Oct 2026). Builds on 23 of its 42 references that are in the map. First posted on arXiv 17 Sep 2021.
Builds on
23 of 42 references.
References · 23
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- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
- 2019PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Textcited by 182
- 2017Variational Reasoning for Question Answering with Knowledge Graphcited by 170
- 2020Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Basescited by 169
- 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 167
- 2015Large-scale Simple Question Answering with Memory Networkscited by 127
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- 2021Case-based Reasoning for Natural Language Queries over Knowledge Basescited by 107
- 2016Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervisioncited by 101
11 more
- 2017Abstract Syntax Networks for Code Generation and Semantic Parsingcited by 92
- 2020Efficient One-Pass End-to-End Entity Linking for Questionscited by 76
- 2021TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graphcited by 60
- 2020SPARQA: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Basescited by 47
- 2019UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answeringcited by 37
- 2020Scalable Neural Methods for Reasoning With a Symbolic Knowledge Basecited by 32
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Citing papers per year: 2021: 1; 2022: 13; 2023: 24; 2024: 22; 2025: 18; 2026: 8.
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