---
title: "Who cites Reuse, Don't Retrain: A Recipe — 32 citing papers"
description: "32 papers of the Elamur Research library cite «Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reuse, Don't Retrain: A Recipe for Continued…](https://md.research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/) / cited by

# Who cites «Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models»

32 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 «Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models»](https://md.research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/)

1. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
2. [**LLM Pruning and Distillation in Practice: The Minitron Approach arXiv:2408.11796**Sharath Turuvekere Sreenivas, Saurav Muralidharan, Raviraj Joshi, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/sreenivas-2024-llm-pruning-distillation-practice-minitron/)
3. **[Towards Effective and Efficient Continual Pre-training of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-effective-efficient-continual-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.*2025 · 29 citations*
4. **[WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback](https://md.research.elamur.ai/free/en/papers/shi-2026-wildfeedback-aligning-llms-situ-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiwei Shi, Zhuoer Wang, Longqi Yang, et al.*2026 · 9 citations*
5. **[Building LLMs Like LEGO: Two-dimensional Architecture Reassembly of Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-building-llms-like-lego-two/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Wu, Yu Zhou, KC Tan*2026 · 1 citation*
6. **[Disentangling Continued Pre-Training: Attention-Driven Routing and Semantic Hub Preservation in Language Adaptation](https://md.research.elamur.ai/free/en/papers/tran-2026-disentangling-continued-pre-training-attention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Khanh-Tung Tran, Vinh-Khanh Tran, Barry O'Sullivan, et al.*2026 · 1 citation*
7. **[Entropy Scheduling in Reinforcement Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-entropy-scheduling-reinforcement-learning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjin Wang, Howe Tissue, Lu Wang, et al.*2026*
8. **[GUI0: Self-Evolving Foundational GUI Agents in Super App Ecosystems](https://md.research.elamur.ai/free/en/papers/wang-2026-gui0-self-evolving-foundational-gui/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi Wang, Wei Dai, Kyle Qiao, et al.*2026*
9. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
10. [**Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training arXiv:2608.30609**Lukas Borggren, Jenny Kunz, Marco Kuhlmann*2026*](https://md.research.elamur.ai/free/en/papers/borggren-2026-reading-news-adapting-large-language/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/) — Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models