---
title: "Who cites UltraIF: Advancing Instruction Following from the Wild"
description: "6 papers of the Elamur Research library cite «UltraIF: Advancing Instruction Following from the Wild», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/cited-by/"
---
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# Who cites «UltraIF: Advancing Instruction Following from the Wild»

6 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 «UltraIF: Advancing Instruction Following from the Wild»](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/)

1. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
2. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
3. **[GATEAU: Selecting Influential Samples for Long Context Alignment](https://md.research.elamur.ai/free/en/papers/si-2025-gateau-selecting-influential-samples-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 5 citations*
4. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/) — UltraIF: Advancing Instruction Following from the Wild