---
title: "Who cites Identifying Causal Relations — 51 citing papers"
description: "51 papers of the Elamur Research library cite «Identifying Causal Relations Using Parallel Wikipedia Articles», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/hidey-2016-identifying-causal-relations-parallel-wikipedia/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Identifying Causal Relations Using Parallel…](https://md.research.elamur.ai/free/en/papers/hidey-2016-identifying-causal-relations-parallel-wikipedia/) / cited by

# Who cites «Identifying Causal Relations Using Parallel Wikipedia Articles»

51 papers of our library cite it (of the 141,840 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Identifying Causal Relations Using Parallel Wikipedia Articles»](https://md.research.elamur.ai/free/en/papers/hidey-2016-identifying-causal-relations-parallel-wikipedia/)

1. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
2. **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 131 citations*
3. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/hidey-2016-identifying-causal-relations-parallel-wikipedia/) — Identifying Causal Relations Using Parallel Wikipedia Articles