---
title: "Who cites Measuring Data Diversity for — 6 citing papers"
description: "6 papers of the Elamur Research library cite «Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric»…"
canonical: "https://research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Measuring Data Diversity for Instruction Tuning…](https://md.research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/) / cited by

# Who cites «Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric»

6 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 «Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric»](https://md.research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/)

1. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations*
2. **[SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe](https://md.research.elamur.ai/free/en/papers/xiao-2026-sftmix-elevating-language-model-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Xiao, Shujian Zhang, Marzyeh Ghassemi, et al.*2026 · 3 citations*
3. **[Task-Aware LLM Routing with Multi-Level Task-Profile-Guided Data Synthesis for Cold-Start Scenarios](https://md.research.elamur.ai/free/en/papers/liu-2026-task-aware-llm-routing-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Liu, Bin Zou, Kecheng Chen, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/) — Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric