---
title: "Who cites Xinlu Zhang — 156 papers of our library"
description: "156 papers of the Elamur Research library cite the works of Xinlu Zhang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xinlu-zhang/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xinlu-zhang/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Xinlu Zhang](https://md.research.elamur.ai/free/en/authors/xinlu-zhang/) / cited by

# Who cites Xinlu Zhang

156 citations of their works from 156 papers of our library (of the 149,439 whose bibliographies we read) · 44 with a page here, the most cited first · [← Xinlu Zhang](https://md.research.elamur.ai/free/en/authors/xinlu-zhang/)

1. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models arXiv:2304.01852 · Meta-Radiology (2023)100,017**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 940 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
2. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 780 citations*
3. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models arXiv:2309.12284**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 565 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
4. [**A Categorical Archive of ChatGPT Failures arXiv:2302.03494**Ali Borji*2023 · 559 citations*](https://md.research.elamur.ai/free/en/papers/borji-2023-categorical-archive-chatgpt-failures/)
5. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 422 citations*
6. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*
7. **[Teaching Small Language Models to Reason](https://md.research.elamur.ai/free/en/papers/magister-2023-teaching-small-language-models-reason/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, et al.*2023 · 343 citations*
8. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes arXiv:2306.13649**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 299 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
9. [**Is ChatGPT a Good NLG Evaluator? A Preliminary Study arXiv:2303.04048**Jiaan Wang, Yunlong Liang, Fandong Meng, et al.*2023 · 287 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-chatgpt-good-nlg-evaluator-preliminary/)
10. [**A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models arXiv:2303.10420**Junjie Ye, Xuanting Chen, Nuo Xu, et al.*2023 · 283 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-comprehensive-capability-analysis-gpt-3/)
11. [**Measuring Faithfulness in Chain-of-Thought Reasoning arXiv:2307.13702**Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.*2023 · 262 citations*](https://md.research.elamur.ai/free/en/papers/lanham-2023-measuring-faithfulness-chain-thought-reasoning/)
12. [**Specializing Smaller Language Models towards Multi-Step Reasoning arXiv:2301.12726**Yao Fu, Hao Peng, Litu Ou, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-specializing-smaller-language-models-towards/)
13. **[Distilling Reasoning Capabilities into Smaller Language Models](https://md.research.elamur.ai/free/en/papers/shridhar-2023-distilling-reasoning-capabilities-into-smaller/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan*2023 · 219 citations*
14. [**ChatGPT as a Factual Inconsistency Evaluator for Text Summarization arXiv:2303.15621**Zheheng Luo, Qianqian Xie, Sophia Ananiadou*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-chatgpt-factual-inconsistency-evaluator-text/)
15. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
16. **[SCOTT: Self-Consistent Chain-of-Thought Distillation](https://md.research.elamur.ai/free/en/papers/wang-2023-scott-self-consistent-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peifeng Wang, Zhengyang Wang, Zheng Li, et al.*2023 · 146 citations*
17. [**Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation arXiv:2304.01746**Tao Fang, Shu Yang, Kaixin Lan, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/fang-2023-chatgpt-highly-fluent-grammatical-error/)
18. **[Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.*2023 · 140 citations*
19. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
20. [**ChatGPT or Grammarly? Evaluating ChatGPT on Grammatical Error Correction Benchmark arXiv:2303.13648**Haoran Wu, Wenxuan Wang, Yuxuan Wan, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-chatgpt-grammarly-evaluating-chatgpt-grammatical/)
21. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
22. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
23. **[On Learning to Summarize with Large Language Models as References](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yixin Liu, Kejian Shi, Katherine He, et al.*2024 · 94 citations*
24. **[Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/paul-2024-making-reasoning-matter-measuring-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debjit Paul, Robert West, Antoine Bosselut, et al.*2024 · 79 citations*
25. **[Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks](https://md.research.elamur.ai/free/en/papers/kang-2023-knowledge-augmented-reasoning-distillation-small/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Minki Kang, Seanie Lee, Jinheon Baek, et al.*2023 · 71 citations*
26. [**Learning From Mistakes Makes LLM Better Reasoner arXiv:2310.20689**Shengnan An, Zexiong Ma, Zeqi Lin, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-learning-mistakes-makes-llm-better/)
27. **[SatLM: Satisfiability-Aided Language Models Using Declarative Prompting](https://md.research.elamur.ai/free/en/papers/ye-2023-satlm-satisfiability-aided-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Qiaochu Chen, Isil Dillig, et al.*2023 · 62 citations*
28. [**ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer arXiv:2306.07799**Dongqi Liu, Vera Demberg*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-chatgpt-vs-human-authored-text/)
29. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
30. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
31. **[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*
32. **[EXCGEC: A Benchmark for Edit-Wise Explainable Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ye-2024-excgec-benchmark-edit-wise-explainable/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jingheng Ye, Shang Qin, Yinghui Li, et al.*2024 · 15 citations*
33. [**Evaluating the Capability of Large-scale Language Models on Chinese Grammatical Error Correction Task arXiv:2307.03972**Fanyi Qu, Chenming Tang, Yunfang Wu*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/qu-2023-evaluating-capability-large-scale-language/)
34. **[QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-qcrd-quality-guided-contrastive-rationale/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Wang, Zhaowei Li, Qi Xu, et al.*2025 · 13 citations*
35. **[SKIntern: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models](https://md.research.elamur.ai/free/en/papers/liao-2025-skintern-internalizing-symbolic-knowledge-distilling/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Huanxuan Liao, Shizhu He, Yupu Hao, et al.*2025 · 12 citations*
36. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
37. **[Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning](https://md.research.elamur.ai/free/en/papers/bi-2025-enhancing-reasoning-capabilities-small-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jing Bi, Yuting Wu, Weiwei Xing, et al.*2025 · 8 citations*
38. **[LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/hong-2025-litex-linguistic-taxonomy-explanations-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pingjun Hong, Beiduo Chen, Siyao Peng, et al.*2025 · 8 citations*
39. [**TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation arXiv:2503.04872**Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-tinyr1-32b-preview-boosting-accuracy/)
40. **[Preference Learning Unlocks LLMs' Psycho-Counseling Skills](https://md.research.elamur.ai/free/en/papers/zhang-2026-preference-learning-unlocks-llms-psycho/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mian Zhang, Shaun M. Eack, Zhiyu Chen*2026 · 2 citations*
41. **[Deputy: Accelerating Large Language Model Inference with Dynamic Low-Rank Substitution](https://md.research.elamur.ai/free/en/papers/zhou-2026-deputy-accelerating-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuhua Zhou, Shichao Weng, Changhai Zhou, et al.*2026 · 1 citation*
42. **[PsychEval: A Multi-Session and Multi-Therapy Benchmark for High-Realism AI Psychological Counselor](https://md.research.elamur.ai/free/en/papers/pan-2026-psycheval-multi-session-multi-therapy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qianjun Pan, Junyi Wang, Jie Zhou, et al.*2026 · 1 citation*
43. **[Tailored Emotional LLM-Supporter: Enhancing Cultural Sensitivity](https://md.research.elamur.ai/free/en/papers/liu-2026-tailored-emotional-llm-supporter-enhancing/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chen Cecilia Liu, Hiba Arnaout, Nils Kovačić, et al.*2026 · 1 citation*
44. **[NSF-CoT: Neuro-Symbolic Formal Verification of Chain-of-Thought Faithfulness in Contextual Question Answering](https://md.research.elamur.ai/free/en/papers/pramanik-2026-nsf-cot-neuro-symbolic-formal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vishal Pramanik, Maisha Maliha, Nathaniel D. Bastian, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/xinlu-zhang/) — Xinlu Zhang