---
title: "Who cites DsDm: Model-Aware Dataset — 29 citing papers"
description: "29 papers of the Elamur Research library cite «DsDm: Model-Aware Dataset Selection with Datamodels», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/engstrom-2024-dsdm-model-aware-dataset-selection/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DsDm: Model-Aware Dataset Selection with…](https://md.research.elamur.ai/free/en/papers/engstrom-2024-dsdm-model-aware-dataset-selection/) / cited by

# Who cites «DsDm: Model-Aware Dataset Selection with Datamodels»

29 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «DsDm: Model-Aware Dataset Selection with Datamodels»](https://md.research.elamur.ai/free/en/papers/engstrom-2024-dsdm-model-aware-dataset-selection/)

1. [**LESS: Selecting Influential Data for Targeted Instruction Tuning arXiv:2402.04333**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 178 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
2. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
3. [**Instruction Mining: Instruction Data Selection for Tuning Large Language Models arXiv:2307.06290**Yihan Cao, Yanbin Kang, Chi Wang, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-instruction-mining-instruction-data-selection/)
4. [**Rho-1: Not All Tokens Are What You Need arXiv:2404.07965**Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-rho-1-all-tokens-need/)
5. [**RegMix: Data Mixture as Regression for Language Model Pre-training arXiv:2407.01492**Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-regmix-data-mixture-regression-language/)
6. [**How to Train Data-Efficient LLMs arXiv:2402.09668**Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/sachdeva-2024-train-data-efficient-llms/)
7. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On arXiv:2407.08348**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
8. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
9. **[Data Efficient RLVR via Off-Policy Influence Guidance](https://md.research.elamur.ai/free/en/papers/zhu-2026-data-efficient-rlvr-off-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erle Zhu, Dazhi Jiang, Yuan Wang, et al.*2026*
10. **[Perplexity-Aware Data Scaling Law: Perplexity Landscapes Predict Performance for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/liu-2026-perplexity-aware-data-scaling-law/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Liu, Hao Zhu, Xiaoyan Yang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/engstrom-2024-dsdm-model-aware-dataset-selection/) — DsDm: Model-Aware Dataset Selection with Datamodels