---
title: "Who cites Yin Zhang — 81 papers of our library"
description: "81 papers of the Elamur Research library cite the works of Yin Zhang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yin-zhang/cited-by/"
---
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# Who cites Yin Zhang

82 citations of their works from 81 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← Yin Zhang](https://md.research.elamur.ai/free/en/authors/yin-zhang/)

1. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
2. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 306 citations*
3. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
4. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
5. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
6. **[Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving](https://md.research.elamur.ai/free/en/papers/quan-2024-verification-refinement-natural-language-explanations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Quan, Marco Valentino, Louise A. Dennis, et al.*2024 · 52 citations*
7. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/)
8. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
9. [**Towards Reasoning Ability of Small Language Models arXiv:2502.11569**Gaurav Srivastava, Shuxiang Cao, Xuan Wang*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2025-towards-reasoning-ability-small-language/)
10. **[ToDi: Token-wise Distillation via Fine-Grained Divergence Control](https://md.research.elamur.ai/free/en/papers/jung-2025-todi-token-wise-distillation-fine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seongryong Jung, Suwan Yoon, DongGeon Kim, et al.*2025 · 12 citations*
11. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
12. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations*
13. **[Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better](https://md.research.elamur.ai/free/en/papers/wang-2026-autoregressive-semantic-visual-reconstruction-helps/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dianyi Wang, Wei Song, Yikun Wang, et al.*2026 · 7 citations*
14. **[Through the Valley: Path to Effective Long CoT Training for Small Language Models](https://md.research.elamur.ai/free/en/papers/luo-2025-through-valley-path-effective-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Luo, Jiaxi Li, Chen Huang, et al.*2025 · 7 citations*
15. **[Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs](https://md.research.elamur.ai/free/en/papers/zhou-2026-flattery-motion-benchmarking-analyzing-sycophancy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.*2026 · 6 citations*
16. **[INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMs](https://md.research.elamur.ai/free/en/papers/yangjunqi-2026-infact-diagnostic-benchmark-induced-faithfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yangjunqi, Yuecong Min, Jie Zhang, et al.*2026 · 5 citations*
17. **[Interleaved Latent Visual Reasoning with Selective Perceptual Modeling](https://md.research.elamur.ai/free/en/papers/dong-2026-interleaved-latent-visual-reasoning-selective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuai Dong, Siyuan Wang, Xingyu Liu, et al.*2026 · 5 citations*
18. **[MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration](https://md.research.elamur.ai/free/en/papers/zhu-2026-medmcp-calc-benchmarking-llms-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yakun Zhu, Yutong Huang, Shengqian Qin, et al.*2026 · 2 citations*
19. **[Unveiling the Deficiencies of Pre-trained Text-and-Layout Models in Real-world Visually-rich Document Information Extraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-unveiling-deficiencies-pre-trained-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chong Zhang, Yixi Zhao, Yulu Xie, et al.*2026 · 1 citation*
20. **[MARD: Module-Aware Reasoning Distillation for Language Models with Adaptive Supervision](https://md.research.elamur.ai/free/en/papers/yang-2026-mard-module-aware-reasoning-distillation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Yang, Jianjun Li, Zhibo Zhang, et al.*2026*
21. **[Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies](https://md.research.elamur.ai/free/en/papers/ye-2026-teaching-language-models-check-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Ye, Raul Santos-Rodriguez, Edwin Simpson*2026*

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

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