---
title: "Who cites Deriving a Web-Scale Common Sense Fact Database"
description: "9 papers of the Elamur Research library cite «Deriving a Web-Scale Common Sense Fact Database», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/tandon-2011-deriving-web-scale-common-sense/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Deriving a Web-Scale Common Sense Fact Database](https://md.research.elamur.ai/free/en/papers/tandon-2011-deriving-web-scale-common-sense/) / cited by

# Who cites «Deriving a Web-Scale Common Sense Fact Database»

9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «Deriving a Web-Scale Common Sense Fact Database»](https://md.research.elamur.ai/free/en/papers/tandon-2011-deriving-web-scale-common-sense/)

1. **[FEVER: a Large-scale Dataset for Fact Extraction and VERification](https://md.research.elamur.ai/free/en/papers/thorne-2018-fever-large-scale-dataset-fact/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**James Thorne, Andreas Vlachos, Christos Christodoulopoulos, et al.*2018 · 2,221 citations*
2. **[Relation Classification via Multi-Level Attention CNNs](https://md.research.elamur.ai/free/en/papers/wang-2016-relation-classification-multi-level-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linlin Wang, Zhu Cao, Gerard de Melo, et al.*2016 · 578 citations*
3. **[NaturalLI: Natural Logic Inference for Common Sense Reasoning](https://md.research.elamur.ai/free/en/papers/angeli-2014-naturalli-natural-logic-inference-common/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabor Angeli, Christopher D. Manning*2014 · 150 citations*
4. **[Commonsense in Parts: Mining Part-Whole Relations from the Web and Image Tags](https://md.research.elamur.ai/free/en/papers/tandon-2016-commonsense-parts-mining-part-whole/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Niket Tandon, Charles Hariman, Jacopo Urbani, et al.*2016 · 31 citations*

5 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/tandon-2011-deriving-web-scale-common-sense/) — Deriving a Web-Scale Common Sense Fact Database
