---
title: "Who cites The Unreasonable Effectiveness — 18 citing papers"
description: "18 papers of the Elamur Research library cite «The Unreasonable Effectiveness of Easy Training Data for Hard Tasks», found in their…"
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---
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# Who cites «The Unreasonable Effectiveness of Easy Training Data for Hard Tasks»

18 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «The Unreasonable Effectiveness of Easy Training Data for Hard Tasks»](https://md.research.elamur.ai/free/en/papers/hase-2024-unreasonable-effectiveness-easy-training-data/)

1. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
2. **[Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision](https://md.research.elamur.ai/free/en/papers/sun-2024-easy-hard-generalization-scalable-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhiqing Sun, Longhui Yu, Yikang Shen, et al.*2024 · 51 citations*
3. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/hase-2024-unreasonable-effectiveness-easy-training-data/) — The Unreasonable Effectiveness of Easy Training Data for Hard Tasks