---
title: "Who cites Wei Cheng — 106 papers of our library"
description: "106 papers of the Elamur Research library cite the works of Wei Cheng, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/wei-cheng/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/wei-cheng/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Wei Cheng](https://md.research.elamur.ai/free/en/authors/wei-cheng/) / cited by

# Who cites Wei Cheng

106 citations of their works from 106 papers of our library (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · [← Wei Cheng](https://md.research.elamur.ai/free/en/authors/wei-cheng/)

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. [**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/)
3. **[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*
4. [**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/)
5. [**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/)
6. [**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/)
7. [**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/)
8. [**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/)
9. [**Qwen-Image Technical Report arXiv:2508.02324**Chenfei Wu, Jiahao Li, Jingren Zhou, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-qwen-image-technical-report/)
10. [**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/)
11. [**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/)
12. [**Baichuan-M2: Scaling Medical Capability with Large Verifier System arXiv:2509.02208**Chengfeng Dou, Chong Liu, Fan Yang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-m2-baichuan-m2-scaling-medical/)
13. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
14. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
15. [**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/)
16. **[DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-diagnosisarena-benchmarking-diagnostic-reasoning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yakun Zhu, Zhongzhen Huang, Linjie Mu, et al.*2026 · 7 citations*
17. **[The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics Analysis](https://md.research.elamur.ai/free/en/papers/wei-2026-evolution-thought-tracking-llm-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Wei, Liang Pang, Jiahao Liu, et al.*2026 · 6 citations*
18. **[Unified Thinker: A General Reasoning Core for Image Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-unified-thinker-general-reasoning-core/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sashuai Zhou, Qiang Zhou, Jijin Hu, et al.*2026 · 3 citations*
19. [**Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making arXiv:2602.06570**Chengfeng Dou, Fan Yang, Fei Li, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-m3-baichuan-m3-modeling-clinical/)
20. **[PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics](https://md.research.elamur.ai/free/en/papers/shen-2026-psychethicsbench-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaling Shen, Stephanie Fong, Yiwen Jiang, et al.*2026 · 2 citations*
21. **[Diffusion with Truncated Blocks: Fast and High-Quality Text Generation using Truncated Block Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffusion-truncated-blocks-fast-high/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Weiyu Chen, James Kwok*2026*
22. **[I2E: From Image Pixels to Actionable Interactive Environments for Text-Guided Image Editing](https://md.research.elamur.ai/free/en/papers/yu-2026-i2e-image-pixels-actionable-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinghan Yu, Junhao Xiao, Chenyu Zhu, et al.*2026*
23. **[MSVBench: Towards Human-Level Evaluation of Multi-Shot Video Generation](https://md.research.elamur.ai/free/en/papers/shi-2026-msvbench-human-level-evaluation-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoyuan Shi, Yunxin li, Nanhao Deng, et al.*2026*
24. **[Towards Unified Multimodal Large Language Models: A survey](https://md.research.elamur.ai/free/en/papers/ma-2026-unified-multimodal-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Ma, Yitian Zhang, Yun Fu*2026*
25. **[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*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/wei-cheng/) — Wei Cheng
