🔗 Who cites «Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models»

88 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← back to «Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models»

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
3. TIES-Merging: Resolving Interference When Merging ModelsConference on Neural Information Processing Systems (NeurIPS)Prateek Yadav, Derek Tam, Leshem Choshen, et al.2023 · 324 citations
4. Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language ModelsarXiv:2405.01535Seungone Kim, Juyoung Suk, Shayne Longpre, et al.2024 · 234 citations
5. Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingarXiv:2310.11564Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.2023 · 102 citations
6. Dataless Knowledge Fusion by Merging Weights of Language ModelsarXiv:2212.09849Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, et al.2022 · 101 citations
7. Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewardsConference on Neural Information Processing Systems (NeurIPS)Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.2023 · 90 citations
8. Knowledge Fusion of Large Language ModelsarXiv:2401.10491Fanqi Wan, Xinting Huang, Deng Cai, et al.2024 · 82 citations
9. Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and OpportunitiesarXiv:2408.07666Enneng Yang, Li Shen, Guibing Guo, et al.2024 · 79 citations
10. ReFT: Representation Finetuning for Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.2024 · 74 citations
11. Exploring the Benefits of Training Expert Language Models over Instruction TuningarXiv:2302.03202Joel Jang, Seungone Kim, Seonghyeon Ye, et al.2023 · 63 citations
12. Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticAnnual Meeting of the Association for Computational Linguistics (ACL)Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria2024 · 59 citations
13. Breaking the Curse of Multilinguality with Cross-lingual Expert Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Terra Blevins, Tomasz Limisiewicz, Suchin Gururangan, et al.2024 · 42 citations
14. Personalized Pieces: Efficient Personalized Large Language Models through Collaborative EffortsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhaoxuan Tan, Zheyuan Liu, Meng Jiang2024 · 40 citations
15. Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language ModelsarXiv:2305.09955Shangbin Feng, Weijia Shi, Yuyang Bai, et al.2023 · 35 citations
16. When One LLM Drools, Multi-LLM Collaboration RulesAnnual Meeting of the Association for Computational Linguistics (ACL)Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.2026 · 14 citations
17. Cross-Lingual Auto Evaluation for Assessing Multilingual LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Sumanth Doddapaneni, Mohammed Safi Ur Rahman Khan, Dilip Venkatesh, et al.2025 · 11 citations
18. TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge DistillationarXiv:2503.04872Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.2025 · 7 citations
19. Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge InjectionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuwei Zhang, Wenhao Yu, Shangbin Feng, et al.2026 · 4 citations
20. ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource SettingsFindings of the Association for Computational LinguisticsJiaxing Liu, Qi Qi, Haifeng Sun, et al.2026
21. TARo: Token-level Adaptive Routing for LLM Test-time AlignmentFindings of the Association for Computational LinguisticsArushi Rai, Qiang Zhang, Hanqing Zeng, et al.2026

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

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