---
title: "Who cites Mingyang Song — 105 papers of our library"
description: "105 papers of the Elamur Research library cite the works of Mingyang Song, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/mingyang-song/cited-by/"
---
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# Who cites Mingyang Song

110 citations of their works from 105 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← Mingyang Song](https://md.research.elamur.ai/free/en/authors/mingyang-song/)

1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
2. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
3. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
4. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
5. [**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/)
6. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
7. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
8. **[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*
9. [**NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens arXiv:2403.12766**Cunxiang Wang, Ruoxi Ning, Boqi Pan, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-novelqa-benchmarking-question-answering-documents/)
10. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
11. **[R-PRM: Reasoning-Driven Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/she-2025-r-prm-reasoning-driven-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuaijie She, Junxiao Liu, Yifeng Liu, et al.*2025 · 18 citations*
12. [**Hunyuan-MT Technical Report arXiv:2509.05209**Mao Zheng, Zheng Li, Bingxin Qu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-hunyuan-mt-technical-report/)
13. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
14. **[Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study](https://md.research.elamur.ai/free/en/papers/song-2025-can-many-shot-context-learning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mingyang Song, Mao Zheng, Xuan Luo*2025 · 9 citations*
15. **[ViLBench: A Suite for Vision-Language Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/tu-2025-vilbench-suite-vision-language-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoqin Tu, Weitao Feng, Hardy Chen, et al.*2025 · 9 citations*
16. **[Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation](https://md.research.elamur.ai/free/en/papers/tian-2026-beyond-literal-mapping-benchmarking-improving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.*2026 · 5 citations*
17. **[Test-Time Scaling of Reasoning Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/li-2026-test-time-scaling-reasoning-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zihao Li, Shaoxiong Ji, Jörg Tiedemann*2026 · 5 citations*
18. **[Beyond Outcome Verification: Verifiable Process Reward Models for Structured Reasoning](https://md.research.elamur.ai/free/en/papers/pronesti-2026-beyond-outcome-verification-verifiable-process/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Massimiliano Pronesti, Anya Belz, Yufang Hou*2026 · 2 citations*
19. **[C2-Faith: Benchmarking LLM Judges for Causal and Coverage Faithfulness in Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/mittal-2026-c2-faith-benchmarking-llm-judges/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Avni Mittal, Rauno Arike*2026 · 2 citations*
20. **[GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-gm-prm-generative-multimodal-process/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Jianghangfan Zhang, Yibo Yan, Kening Zheng, et al.*2026 · 2 citations*
21. **[Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math](https://md.research.elamur.ai/free/en/papers/pandit-2026-hard2verify-step-level-verification-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.*2026 · 2 citations*
22. **[Mending the Holes: Mitigating Reward Hacking in Reinforcement Learning for Multilingual Translation](https://md.research.elamur.ai/free/en/papers/liu-2026-mending-holes-mitigating-reward-hacking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifeng Liu, Siqi Ouyang, Yatish H R, et al.*2026 · 2 citations*
23. **[Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations](https://md.research.elamur.ai/free/en/papers/tan-2026-remedy-r-generative-reasoning-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary, et al.*2026 · 2 citations*
24. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
25. **[IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-rewardbench-benchmarking-judge-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
26. **[NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/miao-2026-neoamt-neologism-aware-agentic-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongtao Miao, Kaiyan Zhao, Masaaki Nagata, et al.*2026 · 1 citation*
27. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation*
28. **[RAFFLES: Reasoning-based Attribution of Faults for LLM Systems](https://md.research.elamur.ai/free/en/papers/zhu-2026-raffles-reasoning-based-attribution-faults/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chenyang Zhu, Spencer Hong, Jingyu Wu, et al.*2026 · 1 citation*
29. **[A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage](https://md.research.elamur.ai/free/en/papers/zheng-2026-comprehensive-survey-process-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Congmin Zheng, Jiachen Zhu, Zhuoying Ou, et al.*2026*
30. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
31. **[CEMT:Controllable Element-Oriented Machine Translation via Structured Linguistic Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2026-cemt-controllable-element-oriented-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingling Shi, Haoyu Jin, Ruiyu Fang, et al.*2026*
32. **[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*
33. **[FeedTrans: Enhance Machine Translation via Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-feedtrans-enhance-machine-translation-feedback/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.*2026*
34. **[GenProve: Learning to Generate Text with Fine-Grained Provenance](https://md.research.elamur.ai/free/en/papers/wei-2026-genprove-learning-generate-text-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingxuan Wei, Xingyue Wang, Yanghaoyu Liao, et al.*2026*
35. **[NeedleChain: Measuring Intact Context Comprehension Capability of Large Language Models](https://md.research.elamur.ai/free/en/papers/moon-2026-needlechain-measuring-intact-context-comprehension/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyeonseok Moon, Heuiseok Lim*2026*
36. **[NiuTrans.LMT: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-niutrans-lmt-inclusive-scalable-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yingfeng Luo, Ziqiang Xu, Yuxuan Ouyang, et al.*2026*
37. **[PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shen-2026-pegrl-improving-machine-translation-post/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunzhi Shen, Hao Zhou, Xin Huang, et al.*2026*
38. **[Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-performance-low-resource-annotation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qi Zhang, Fangping Lan, Cornelia Caragea, et al.*2026*
39. **[Simultaneous Speech-to-Text Translation Web Application for Estonian](https://md.research.elamur.ai/free/en/papers/podziubanchuk-2026-simultaneous-speech-text-translation-web/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bohdan Podziubanchuk, Aivo Olev, Jiaming Kong, et al.*2026*
40. **[Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation](https://md.research.elamur.ai/free/en/papers/ye-2026-translation-thought-difficulty-adaptive-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongshi Ye, Biao Fu, Chongxuan Huang, et al.*2026*

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

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