---
title: "Who cites Shuo Yang — 185 papers of our library"
description: "185 papers of the Elamur Research library cite the works of Shuo Yang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/shuo-yang/cited-by/"
---
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# Who cites Shuo Yang

186 citations of their works from 185 papers of our library (of the 149,439 whose bibliographies we read) · 49 with a page here, the most cited first · [← Shuo Yang](https://md.research.elamur.ai/free/en/authors/shuo-yang/)

1. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools arXiv:2406.12793**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 691 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
2. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
3. [**Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference arXiv:2403.04132**Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.*2024 · 546 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2024-chatbot-arena-open-platform-evaluating/)
4. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
5. **[PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU](https://md.research.elamur.ai/free/en/papers/song-2023-powerinfer-fast-large-language-model/) [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/)**Yixin Song, Zeyu Mi, Haotong Xie, et al.*2023 · 272 citations*
6. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
7. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
8. **[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*
9. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
10. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
11. [**ServerlessLLM: Low-Latency Serverless Inference for Large Language Models arXiv:2401.14351**Yao Fu, Leyang Xue, Yeqi Huang, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-serverlessllm-low-latency-serverless-inference/)
12. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations*
13. [**Do Membership Inference Attacks Work on Large Language Models? arXiv:2402.07841**Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/duan-2024-membership-inference-attacks-work-large/)
14. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
15. [**OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data arXiv:2410.01560**Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/toshniwal-2024-openmathinstruct-2-accelerating-ai-math/)
16. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 76 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
17. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
18. **[MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures](https://md.research.elamur.ai/free/en/papers/ni-2024-mixeval-deriving-wisdom-crowd-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.*2024 · 47 citations*
19. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations*
20. [**Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models arXiv:2404.02823**Haoran Sun, Lixin Liu, Junjie Li, et al.*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-conifer-improving-complex-constrained-instruction/)
21. [**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/)
22. **[CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.*2025 · 38 citations*
23. [**OpenCodeReasoning: Advancing Data Distillation for Competitive Coding arXiv:2504.01943**Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2025-opencodereasoning-advancing-data-distillation-competitive/)
24. **[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*
25. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*
26. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
27. **[NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Queries](https://md.research.elamur.ai/free/en/papers/zhang-2024-naturalcodebench-examining-coding-performance-mismatch/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shudan Zhang, Hanlin Zhao, Xiao Liu, et al.*2024 · 17 citations*
28. [**Orion-14B: Open-source Multilingual Large Language Models arXiv:2401.12246**Du Chen, Yi Huang, Xiaopu Li, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-orion-14b-open-source/)
29. [**Jais 2: A Family of Arabic-Centric Open Large Language Models arXiv:2608.13580**Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2026-jais-2-family-arabic-centric/)
30. **[Semantic-Aware Logical Reasoning via a Semiotic Framework](https://md.research.elamur.ai/free/en/papers/zhang-2026-semantic-aware-logical-reasoning-semiotic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunyao Zhang, Xinglang Zhang, Junxi Sheng, et al.*2026 · 13 citations*
31. [**Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation arXiv:2501.14275**Sadegh Mahdavi, Muchen Li, Kaiwen Liu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-leveraging-online-olympiad-level-math/)
32. **[Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://md.research.elamur.ai/free/en/papers/akter-2026-nemotron-crossthink-scaling-self-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.*2026 · 9 citations*
33. **[ATLAS: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-atlas-orchestrating-heterogeneous-models-tools/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Guocheng Zhai, Ruihan Jin, et al.*2026 · 8 citations*
34. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations*
35. **[PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-perm-psychology-grounded-empathetic-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengbing Wang, Wuqiang Zheng, Yang Zhang, et al.*2026 · 8 citations*
36. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
37. **[FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2026-fact-e-causality-inspired-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxi Sun, Aoqi Zuo, Haotian Xie, et al.*2026 · 7 citations*
38. **[UltraIF: Advancing Instruction Following from the Wild](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaikai An, Li Sheng, Ganqu Cui, et al.*2025 · 7 citations*
39. **[Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction](https://md.research.elamur.ai/free/en/papers/shen-2026-metacognitive-self-correction-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Shen, Qi Zhang, Song Wang, et al.*2026 · 3 citations*
40. **[StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-streammeco-long-term-agent-memory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junxi Wang, Te Sun, Jiayi Zhu, et al.*2026 · 3 citations*
41. **[When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/tan-2026-when-flores-bloomz-wrong-cross/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**David Tan, Pinzhen Chen, Josef van Genabith, et al.*2026 · 2 citations*
42. **[MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://md.research.elamur.ai/free/en/papers/qu-2026-matchtir-fine-grained-supervision-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changle Qu, Sunhao Dai, Hengyi Cai, et al.*2026 · 1 citation*
43. **[Test of Time: Rethinking Temporal Signal of Benchmark Contamination](https://md.research.elamur.ai/free/en/papers/zhang-2026-test-time-rethinking-temporal-signal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terry Jingchen Zhang, Gopal Dev, Ning Wang, et al.*2026 · 1 citation*
44. **[UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization](https://md.research.elamur.ai/free/en/papers/lu-2026-ui-copilot-advancing-long-horizon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxi Lu, Fei Tang, Guangyi Liu, et al.*2026 · 1 citation*
45. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
46. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
47. **[Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-examples-automated-thought-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Mingkuan Feng, Shuai Zhang, et al.*2026*
48. **[Cards Against Contamination: TCG-Bench for Difficulty-Scalable Multilingual LLM Reasoning](https://md.research.elamur.ai/free/en/papers/alrashed-2026-cards-against-contamination-tcg-bench/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sultan AlRashed, Jianghui Wang, Francesco Orabona*2026*
49. **[Experience-driven Multi-turn Reinforcement Learning for GUI Agents](https://md.research.elamur.ai/free/en/papers/lu-2026-experience-driven-multi-turn-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxi Lu, Jiabo Ye, Fei Tang, et al.*2026*

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

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