--- title: "Who cites MAP-Neo: Highly Capable and — 42 citing papers" description: "42 papers of the Elamur Research library cite «MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series», found in…" canonical: "https://research.elamur.ai/free/en/papers/zhang-2024-map-neo-highly-capable-transparent/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhang-2024-map-neo-highly-capable-transparent/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MAP-Neo: Highly Capable and Transparent Bilingual…](https://md.research.elamur.ai/free/en/papers/zhang-2024-map-neo-highly-capable-transparent/) / cited by # Who cites «MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series» 42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series»](https://md.research.elamur.ai/free/en/papers/zhang-2024-map-neo-highly-capable-transparent/) 1. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 761 citations* 2. **[The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.*2024 · 434 citations* 3. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations* 4. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations* 5. **[Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Shao, Shengju Qian, Han Xiao, et al.*2024 · 117 citations* 6. [**SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines arXiv:2502.14739**M-A-P Team, Xinrun Du, Yifan Yao, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-supergpqa-scaling-llm-evaluation-across/) 7. [**ReTool: Reinforcement Learning for Strategic Tool Use in LLMs arXiv:2504.11536**Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.*2025 · 88 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/) 8. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations* 9. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations* 10. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/) 11. **[DDK: Distilling Domain Knowledge for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-ddk-distilling-domain-knowledge-efficient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.*2024 · 23 citations* 12. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/) 13. [**A Survey on Latent Reasoning arXiv:2507.06203**Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-survey-latent-reasoning/) 14. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations* 15. **[M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation](https://md.research.elamur.ai/free/en/papers/liu-2025-m2rc-eval-massively-multilingual-repository/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaheng Liu, Ken Deng, Congnan Liu, et al.*2025 · 8 citations* 16. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026* 17. **[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* 18. **[LEDOM: Reverse Language Model](https://md.research.elamur.ai/free/en/papers/yin-2026-ledom-reverse-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xunjian Yin, Sitao Cheng, Yuxi Xie, et al.*2026* 24 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2024-map-neo-highly-capable-transparent/) — MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series