---
title: "Who cites Maximilian Mozes — 174 papers of our library"
description: "174 papers of the Elamur Research library cite the works of Maximilian Mozes, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/maximilian-mozes/cited-by/"
---
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# Who cites Maximilian Mozes

175 citations of their works from 174 papers of our library (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · [← Maximilian Mozes](https://md.research.elamur.ai/free/en/authors/maximilian-mozes/)

1. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
2. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
3. **[Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations](https://md.research.elamur.ai/free/en/papers/wang-2024-math-shepherd-verify-reinforce-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiyi Wang, Lei Li, Zhihong Shao, et al.*2024 · 497 citations*
4. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
5. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
6. **[RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 207 citations*
7. **[How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2024-how-johnny-can-persuade-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Zeng, Hongpeng Lin, Jingwen Zhang, et al.*2024 · 203 citations*
8. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
9. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
10. **[LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://md.research.elamur.ai/free/en/papers/du-2024-llms-assist-nlp-researchers-critique/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiangshu Du, Yibo Wang, Wenting Zhao, et al.*2024 · 71 citations*
11. **[ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence](https://md.research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kevin Wu, Eric Wu, James Zou*2024 · 65 citations*
12. **[Understanding and Mitigating Language Confusion in LLMs](https://md.research.elamur.ai/free/en/papers/marchisio-2024-understanding-mitigating-language-confusion-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kelly Marchisio, Wei-Yin Ko, Alexandre Berard, et al.*2024 · 57 citations*
13. [**ARGS: Alignment as Reward-Guided Search arXiv:2402.01694**Maxim Khanov, Jirayu Burapacheep, Yixuan Li*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/khanov-2024-args-alignment-reward-guided-search/)
14. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/)
15. [**MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks arXiv:2505.03427**Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/daoud-2025-medarabiq-benchmarking-large-language-models/)
16. [**MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning arXiv:2402.11260**Shu Yang; Muhammad Asif Ali; Cheng-Long Wang; Lijie Hu;, Di Wang*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-moral-moe-augmented-lora-llms/)
17. **[Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models](https://md.research.elamur.ai/free/en/papers/gao-2025-shaping-safety-boundaries-understanding-defending/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lang Gao, Jiahui Geng, Xiangliang Zhang, et al.*2025 · 19 citations*
18. [**In-Context Principle Learning from Mistakes arXiv:2402.05403**Tianjun Zhang, Aman Madaan, Luyu Gao, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-context-principle-learning-mistakes/)
19. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations*
20. **[SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence](https://md.research.elamur.ai/free/en/papers/liu-2025-selfelicit-your-language-model-secretly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhining Liu, Rana Ali Amjad, Ravinarayana Adkathimar, et al.*2025 · 11 citations*
21. [**The Trickle-down Impact of Reward (In-)consistency on RLHF arXiv:2309.16155**Lingfeng Shen, Sihao Chen, Linfeng Song, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-trickle-down-impact-reward-consistency/)
22. [**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/)
23. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
24. **[Attention to Non-Adopters](https://md.research.elamur.ai/free/en/papers/zhou-2026-attention-non-adopters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, et al.*2026 · 1 citation*
25. [**Evaluation of Adversarial Robustness in Arabic Language Models arXiv:2607.25814**Anwar Alajmi, Ayed Salman, Imtiaz Ahmad*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alajmi-2026-evaluation-adversarial-robustness-arabic-language/)
26. **[CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG Hallucinations](https://md.research.elamur.ai/free/en/papers/shi-2026-coda-restoring-contextual-dominance-copy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**JinWei Shi, Qizhuo Xie, Qianzi Hou, et al.*2026*
27. **[GRASPrune: Global Gating for Budgeted Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-grasprune-global-gating-budgeted-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyang Wang, Jiangfeng Xiao, Chuan Xiao, et al.*2026*
28. **[KGHaluBench: A Knowledge Graph-Based Hallucination Benchmark for Evaluating the Breadth and Depth of LLM Knowledge](https://md.research.elamur.ai/free/en/papers/robertson-2026-kghalubench-knowledge-graph-based-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alex Robertson, Huizhi Liang, Mahbub Gani, et al.*2026*

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

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