---
title: "Who cites Aligning Large Language Models — 11 citing papers"
description: "11 papers of the Elamur Research library cite «Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Aligning Large Language Models to Follow…](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) / cited by

# Who cites «Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering»

11 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 «Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering»](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/)

1. **[UltraIF: Advancing Instruction Following from the Wild](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaikai An, Li Sheng, Ganqu Cui, et al.*2025 · 7 citations*
2. **[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*
3. **[FaithLens: Detecting and Explaining Faithfulness Hallucination](https://md.research.elamur.ai/free/en/papers/si-2026-faithlens-detecting-explaining-faithfulness-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuzheng Si, Qingyi Wang, Haozhe Zhao, et al.*2026 · 1 citation*
4. **[The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic Truthfulness](https://md.research.elamur.ai/free/en/papers/mao-2026-digital-dunning-kruger-effect-decoupling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueheng Mao, Min Yu, Gengwang Li, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) — Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering