--- title: "Who cites Tong Zhu — 88 papers of our library" description: "88 papers of the Elamur Research library cite the works of Tong Zhu, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/tong-zhu/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tong-zhu/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Tong Zhu](https://md.research.elamur.ai/free/en/authors/tong-zhu/) / cited by # Who cites Tong Zhu 89 citations of their works from 88 papers of our library (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← Tong Zhu](https://md.research.elamur.ai/free/en/authors/tong-zhu/) 1. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Zhu, Xiaoye Qu, Daize Dong, et al.*2024 · 85 citations* 2. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/) 3. **[Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?](https://md.research.elamur.ai/free/en/papers/jin-2025-exploring-concept-depth-how-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mingyu Jin, Qinkai Yu, Jingyuan Huang, et al.*2025 · 36 citations* 4. **[ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use](https://md.research.elamur.ai/free/en/papers/ye-2025-toolhop-query-driven-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Ye, Zhengyin Du, Xuesong Yao, et al.*2025 · 15 citations* 5. **[MCP-Flow: Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools](https://md.research.elamur.ai/free/en/papers/wang-2026-mcp-flow-facilitating-llm-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**WenHao Wang, Peizhi Niu, Zhao Xu, et al.*2026 · 7 citations* 6. [**MoM: Linear Sequence Modeling with Mixture-of-Memories arXiv:2502.13685**Jusen Du, Weigao Sun, Disen Lan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/du-2025-mom-linear-sequence-modeling-mixture/) 7. **[NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/han-2025-nestools-dataset-evaluating-nested-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Han Han, Tong Zhu, Xiang Zhang, et al.*2025 · 7 citations* 8. **[Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2026-sparse-brains-are-also-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Yang, Yujie Wang, Chi Ma, et al.*2026 · 3 citations* 9. **[Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis](https://md.research.elamur.ai/free/en/papers/pei-2026-analytical-ffn-moe-restructuring-activation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zehua Pei, Hui-Ling Zhen, Lancheng Zou, et al.*2026 · 1 citation* 10. **[H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMs](https://md.research.elamur.ai/free/en/papers/tekin-2026-h3fusion-helpful-harmless-honest-fusion/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Selim Furkan Tekin, Fatih Ilhan, Sihao Hu, et al.*2026 · 1 citation* 11. **[TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent](https://md.research.elamur.ai/free/en/papers/sui-2026-tea-bench-systematic-benchmarking-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Sui, Yanyan Zhao, Yulin Hu, et al.*2026 · 1 citation* 12. [**Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving arXiv:2512.10739**Yuzhe Gu, Songyang Gao, Zijian Wu, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/gu-2025-intern-s1-mo-long/) 13. **[ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource Settings](https://md.research.elamur.ai/free/en/papers/liu-2026-modularmoe-fast-llm-customization-parameter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxing Liu, Qi Qi, Haifeng Sun, et al.*2026* 14. **[ODL-TempLLM: Ontology-Guided and Description Logic-Reasoned Temporal Reasoning with LLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-odl-templlm-ontology-guided-description/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinshuo Liu, Cheng Bi, Meng Wang, et al.*2026* 15. **[On the Cultural Anachronism and Temporal Reasoning in Vision Language Models](https://md.research.elamur.ai/free/en/papers/ranjan-2026-cultural-anachronism-temporal-reasoning-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mukul Ranjan, Prince Jha, Khushboo Kumari, et al.*2026* 16. **[Pattern Enhanced Multi-Turn Jailbreaking: Exploiting Structural Vulnerabilities in Large Language Models](https://md.research.elamur.ai/free/en/papers/nihal-2026-pattern-enhanced-multi-turn-jailbreaking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ragib Amin Nihal, Rui Wen, Kazuhiro Nakadai, et al.*2026* 17. **[Survey on System Optimization for Mixture of Experts in the Era of Large Models (大模型时代的混合专家系统优化综述)](https://md.research.elamur.ai/free/en/papers/shi-2025-system-optimization-mixture/) [Journal of Computer Research and Development](https://md.research.elamur.ai/free/en/venues/journal-of-computer-research-and-development/)**Hongzhi Shi (史宏志), Jian Zhao (赵健), Yaqian Zhao (赵雅倩), et al.*2025* 71 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/tong-zhu/) — Tong Zhu