---
title: "Who cites Ming Zhu — 114 papers of our library"
description: "114 papers of the Elamur Research library cite the works of Ming Zhu, found in their bibliographies; the most cited first."
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---
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# Who cites Ming Zhu

119 citations of their works from 114 papers of our library (of the 149,439 whose bibliographies we read) · 30 with a page here, the most cited first · [← Ming Zhu](https://md.research.elamur.ai/free/en/authors/ming-zhu/)

1. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
2. **[CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X](https://md.research.elamur.ai/free/en/papers/zheng-2023-codegeex-pre-trained-model-code/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Qinkai Zheng, Xiao Xia, Xu Zou, et al.*2023 · 465 citations*
3. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
4. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
5. [**OS-ATLAS: A Foundation Action Model for Generalist GUI Agents arXiv:2410.23218**Zhiyong Wu, Zhenyu Wu, Fangzhi Xu, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-os-atlas-foundation-action-model/)
6. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*
7. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
8. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
9. **[APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay](https://md.research.elamur.ai/free/en/papers/prabhakar-2025-apigen-mt-agentic-pipeline-multi/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Akshara Prabhakar, Zuxin Liu, Ming Zhu, et al.*2025 · 36 citations*
10. **[MMLU-CF: A Contamination-free Multi-task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/zhao-2025-mmlu-cf-contamination-free-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qihao Zhao, Yangyu Huang, Tengchao Lv, et al.*2025 · 21 citations*
11. **[NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API Calls](https://md.research.elamur.ai/free/en/papers/basu-2025-nestful-benchmark-evaluating-llms-nested/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kinjal Basu, Ibrahim Abdelaziz, Kiran Kate, et al.*2025 · 16 citations*
12. [**Qwen3-Coder-Next Technical Report arXiv:2603.00729**Ruisheng Cao, Mouxiang Chen, Jiawei Chen, et al.*2026 · 15 citations*](https://md.research.elamur.ai/free/en/papers/cao-2026-qwen3-coder-next-technical/)
13. **[Can a Single Model Master Both Multi-turn Conversations and Tool Use? CoALM: A Unified Conversational Agentic Language Model](https://md.research.elamur.ai/free/en/papers/acikgoz-2025-can-single-model-master-both/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Emre Can Acikgoz, Jeremiah Greer, Akul Datta, et al.*2025 · 13 citations*
14. **[When2Call: When (not) to Call Tools](https://md.research.elamur.ai/free/en/papers/ross-2025-when2call-when-not-call-tools/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hayley Ross, Ameya Sunil Mahabaleshwarkar, Yoshi Suhara*2025 · 11 citations*
15. **[LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangning Zhang, Weiwen Liu, Wenxiang Jiao, et al.*2026 · 6 citations*
16. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
17. **[EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis](https://md.research.elamur.ai/free/en/papers/song-2026-envscaler-scaling-tool-interactive-environments/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoshuai Song, Haofei Chang, Guanting Dong, et al.*2026 · 5 citations*
18. **[Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text](https://md.research.elamur.ai/free/en/papers/xu-2026-unlocking-implicit-experience-synthesizing-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihao Xu, Rumei Li, Jiahuan Li, et al.*2026 · 4 citations*
19. **[Failure makes the agent stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions](https://md.research.elamur.ai/free/en/papers/su-2026-failure-makes-agent-stronger-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junhao Su, Yuanliang Wan, Junwei Yang, et al.*2026 · 2 citations*
20. **[Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User Intents](https://md.research.elamur.ai/free/en/papers/wang-2026-trajectory2task-training-robust-tool-calling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyi Wang, Yuxuan Lu, Yimeng Zhang, et al.*2026 · 2 citations*
21. **[DRAGON: Domain-specific Robust Automatic Data Generation for RAG Optimization](https://md.research.elamur.ai/free/en/papers/shen-2026-dragon-domain-specific-robust-automatic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Shen, Hang Yan, Zhongshi Xing, et al.*2026 · 1 citation*
22. **[Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents](https://md.research.elamur.ai/free/en/papers/monfared-2026-label-consistent-data-generation-aspect/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Mohammad Hossein Akbari Monfared, Lucie Flek, Akbar Karimi*2026 · 1 citation*
23. **[Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors](https://md.research.elamur.ai/free/en/papers/zhang-2026-robust-tool-use-fission-grpo/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiwei Zhang, Fei Zhao, Rui Wang, et al.*2026 · 1 citation*
24. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation*
25. **[TInR: Exploring Tool-Internalized Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-tinr-exploring-tool-internalized-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiancheng Xu, Yongqi Li, Fan Liu, et al.*2026 · 1 citation*
26. **[Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*
27. **[EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios](https://md.research.elamur.ai/free/en/papers/mu-2026-efficienttool-cost-effective-aligning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.*2026*
28. **[FAER: Benchmarking VLMs for Failure-Aware Embodied Reasoning](https://md.research.elamur.ai/free/en/papers/song-2026-faer-benchmarking-vlms-failure-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Song, Kaifeng Liu, Yuanxing Liu, et al.*2026*
29. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*
30. **[U-Fold: Dynamic Intent-Aware Context Folding for User-Centric Agents](https://md.research.elamur.ai/free/en/papers/su-2026-u-fold-dynamic-intent-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Su, Runnan Fang, Yeqiu Li, et al.*2026*

84 more citing papers of our library have no page here yet.

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