---
title: "Who cites The Next Decade in AI: Four — 45 citing papers"
description: "45 papers of the Elamur Research library cite «The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence», found in their…"
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---
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# Who cites «The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence»

45 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence»](https://md.research.elamur.ai/free/en/papers/marcus-2020-next-decade-ai-four/)

1. [**Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks arXiv:2005.11401**Patrick Lewis, Ethan Perez, Aleksandra Piktus, et al.*2020 · 6,256 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-retrieval-augmented-generation-knowledge-intensive/)
2. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
3. [**Out of One, Many: Using Language Models to Simulate Human Samples arXiv:2209.06899**Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, et al.*2022 · 957 citations*](https://md.research.elamur.ai/free/en/papers/argyle-2022-out-one-many-using-language/)
4. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 780 citations*
5. **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.*2023 · 117 citations*
6. **[LAMBADA: Backward Chaining for Automated Reasoning in Natural Language](https://md.research.elamur.ai/free/en/papers/kazemi-2023-lambada-backward-chaining-automated-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.*2023 · 89 citations*
7. **[The Role of Deductive and Inductive Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/cai-2025-role-deductive-inductive-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengkun Cai, Xu Zhao, Haoliang Liu, et al.*2025 · 17 citations*
8. **[Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-dreaming-out-loud-self-synthesis/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce, et al.*2024 · 1 citation*
9. [**SteuerLLM: Local specialized large language model for German tax law analysis arXiv:2602.11081 · Scientific Reports, Volume 16, 2026**Sebastian Wind, Jeta Sopa, Laurin Schmid, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wind-2026-steuerllm-local-specialized-large-language/)

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

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