---
title: "Who cites AdaMerging: Adaptive Model — 54 citing papers"
description: "54 papers of the Elamur Research library cite «AdaMerging: Adaptive Model Merging for Multi-Task Learning», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [AdaMerging: Adaptive Model Merging for Multi-Task…](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/) / cited by

# Who cites «AdaMerging: Adaptive Model Merging for Multi-Task Learning»

54 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «AdaMerging: Adaptive Model Merging for Multi-Task Learning»](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/)

1. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
2. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
3. **[Nature-Inspired Population-Based Evolution of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-nature-inspired-population-based-evolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.*2026 · 8 citations*
4. **[Revisiting Model Interpolation for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-revisiting-model-interpolation-efficient-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiqiang Wu, Runming Yang, Tao Liu, et al.*2026 · 6 citations*
5. **[LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint](https://md.research.elamur.ai/free/en/papers/ma-2025-led-merging-mitigating-safety-utility/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Ma, Dongrui Liu, Qian Chen, et al.*2025 · 5 citations*
6. **[Why Do More Experts Fail? A Theoretical Analysis of Model Merging](https://md.research.elamur.ai/free/en/papers/wang-2026-why-do-more-experts-fail/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijing Wang, Xingle Xu, YongKang Liu, et al.*2026 · 2 citations*
7. **[DivMerge: A divergence-based model merging method for multi-tasking](https://md.research.elamur.ai/free/en/papers/touayouch-2026-divmerge-divergence-based-model-merging/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Brahim Touayouch, Loïc Fosse, Géraldine Damnati, et al.*2026*
8. **[ReasonAny: Incorporating Reasoning Capability to Any Model via Simple and Effective Model Merging](https://md.research.elamur.ai/free/en/papers/yang-2026-reasonany-incorporating-reasoning-capability-any/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyao Yang, Chen Qian, Wen Shen, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/) — AdaMerging: Adaptive Model Merging for Multi-Task Learning