---
title: "Who cites Xianjun Yang — 181 papers of our library"
description: "181 papers of the Elamur Research library cite the works of Xianjun Yang, found in their bibliographies; the most cited first."
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---
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# Who cites Xianjun Yang

181 citations of their works from 181 papers of our library (of the 149,439 whose bibliographies we read) · 49 with a page here, the most cited first · [← Xianjun Yang](https://md.research.elamur.ai/free/en/authors/xianjun-yang/)

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. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
7. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
8. [**Refusal in Language Models Is Mediated by a Single Direction arXiv:2406.11717**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
9. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
10. [**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/)
11. **[MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2023-mm-safetybench-benchmark-safety-evaluation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xin Liu, Yichen Zhu, Jindong Gu, et al.*2023 · 152 citations*
12. [**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/)
13. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
14. [**The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning arXiv:2403.03218**Nathaniel Li, Alexander Pan, Anjali Gopal, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-wmdp-benchmark-measuring-reducing-malicious/)
15. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
16. [**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/)
17. **[Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/wu-2024-janus-decoupling-visual-encoding/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Chengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.*2024 · 112 citations*
18. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
19. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
20. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
21. [**Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications arXiv:2402.05162**Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-assessing-brittleness-safety-alignment-pruning/)
22. [**A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity arXiv:2401.01967**Andrew Lee, Xiaoyan Bai, Itamar Pres, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-mechanistic-understanding-alignment-algorithms-case/)
23. **[Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yang-2024-self-distillation-bridges-distribution-gap/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaorui Yang, Tianyu Pang, Haozhe Feng, et al.*2024 · 63 citations*
24. **[Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic](https://md.research.elamur.ai/free/en/papers/bhardwaj-2024-language-models-are-homer-simpson/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria*2024 · 59 citations*
25. [**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/)
26. [**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/)
27. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
28. **[Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training](https://md.research.elamur.ai/free/en/papers/yuan-2025-refuse-whenever-you-feel-unsafe/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2025 · 19 citations*
29. **[Jailbreaking LLMs with Arabic Transliteration and Arabizi](https://md.research.elamur.ai/free/en/papers/ghanim-2024-jailbreaking-llms-arabic-transliteration-arabizi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, et al.*2024 · 16 citations*
30. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/)
31. [**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/)
32. **[SciVer: Evaluating Foundation Models for Multimodal Scientific Claim Verification](https://md.research.elamur.ai/free/en/papers/wang-2025-sciver-evaluating-foundation-models-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengye Wang, Yifei Shen, Zexi Kuang, et al.*2025 · 11 citations*
33. **[Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2025-beware-your-po-measuring-mitigating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weixiang Zhao, Yulin Hu, Yang Deng, et al.*2025 · 9 citations*
34. **[The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-dark-side-function-calling-pathways/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zihui Wu, Haichang Gao, Jianping He, et al.*2025 · 8 citations*
35. **[Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets](https://md.research.elamur.ai/free/en/papers/hsiung-2026-why-llm-safety-guardrails-collapse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Hsiung, Tianyu Pang, Yung-Chen Tang, et al.*2026 · 4 citations*
36. **[SDD: Self-Degraded Defense against Malicious Fine-tuning](https://md.research.elamur.ai/free/en/papers/chen-2025-sdd-self-degraded-defense-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZiXuan Chen, Weikai Lu, Xin Lin, et al.*2025 · 4 citations*
37. **[CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yi-2026-ctrap-embedding-collapse-trap-safeguard/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Biao Yi, Tiansheng Huang, Baolei Zhang, et al.*2026 · 3 citations*
38. **[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*
39. **[Measuring Human Contribution in AI-Assisted Content Generation](https://md.research.elamur.ai/free/en/papers/xie-2026-measuring-human-contribution-ai-assisted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueqi Xie, Tao Qi, Jingwei Yi, et al.*2026 · 1 citation*
40. **[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*
41. **[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*
42. **[CSULoRA: Closest Safe Update Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/marchenko-2026-csulora-closest-safe-update-low/) [International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security](https://md.research.elamur.ai/free/en/venues/nlpaics/)**Oleksandr Marchenko, Adelaide Danilov, Aria Nourbakhsh, et al.*2026*
43. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026*
44. **[EduMARS: Can Vision-Language Models Grade Like Teachers? Benchmarking Multimodal, Rubric-Based Assessment on Chinese K-12 Answers](https://md.research.elamur.ai/free/en/papers/zhao-2026-edumars-can-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Zhao, Jiashun Chen, Wanting xu, et al.*2026*
45. **[OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment Strategy](https://md.research.elamur.ai/free/en/papers/tang-2026-oasis-mitigating-harmful-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayu Tang, Guowei Peng, Qiuhao Xie, et al.*2026*
46. **[Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not Stable](https://md.research.elamur.ai/free/en/papers/tang-2026-probing-plasticity-correlation-llm-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenheng Tang, Qihua Pan, Jingya Shen, et al.*2026*
47. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*
48. **[The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-art-mis-alignment-how-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Zhang, Hongwei Li, Yun Shen, et al.*2026*
49. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*

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

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