---
title: "Who cites Hugh Zhang — 431 papers of our library"
description: "431 papers of the Elamur Research library cite the works of Hugh Zhang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hugh-zhang/cited-by/"
---
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# Who cites Hugh Zhang

445 citations of their works from 431 papers of our library (of the 141,840 whose bibliographies we read) · 54 with a page here, the most cited first · [← Hugh Zhang](https://md.research.elamur.ai/free/en/authors/hugh-zhang/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,222 citations*
2. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 906 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
3. **[GLTR: Statistical Detection and Visualization of Generated Text](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush*2019 · 693 citations*
4. **[Social Bias Frames: Reasoning about Social and Power Implications of Language](https://md.research.elamur.ai/free/en/papers/sap-2020-social-bias-frames-reasoning-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.*2020 · 681 citations*
5. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 584 citations*
6. [**Towards a Human-like Open-Domain Chatbot arXiv:2001.09977**Daniel Adiwardana, Minh-Thang Luong, David R. So, et al.*2020 · 581 citations*](https://md.research.elamur.ai/free/en/papers/adiwardana-2020-towards-human-like-open-domain/)
7. [**gpt-oss-120b & gpt-oss-20b Model Card arXiv:2508.10925**OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.*2025 · 555 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-gpt-oss-120b-gpt-oss/)
8. [**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/)
9. [**Defending Against Neural Fake News arXiv:1905.12616**Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al.*2019 · 466 citations*](https://md.research.elamur.ai/free/en/papers/zellers-2019-defending-against-neural-fake-news/)
10. **[FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Esin Durmus, He He, Mona Diab*2020 · 352 citations*
11. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 335 citations*
12. [**DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arXiv:2512.02556**DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.*2025 · 333 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-v3-2-pushing/)
13. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 331 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
14. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
15. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools arXiv:2405.20362**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
16. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models arXiv:2410.05229**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
17. [**MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers arXiv:2102.01454**Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, et al.*2021 · 244 citations*](https://md.research.elamur.ai/free/en/papers/pillutla-2021-mauve-measuring-gap-between-neural/)
18. **[Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts](https://md.research.elamur.ai/free/en/papers/clark-2019-sentence-mover-s-similarity-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elizabeth Clark, Asli Celikyilmaz, Noah A. Smith*2019 · 208 citations*
19. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 204 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/)
20. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
21. **[Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias](https://md.research.elamur.ai/free/en/papers/yu-2023-large-language-model-attributed-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.*2023 · 198 citations*
22. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*
23. **[Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eikema-2020-is-map-decoding-all-you/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bryan Eikema, Wilker Aziz*2020 · 165 citations*
24. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models arXiv:2508.06471**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
25. **[Locally Typical Sampling](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 154 citations*
26. **[Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text](https://md.research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, et al.*2022 · 152 citations*
27. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature arXiv:2310.05130**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
28. [**GLUCOSE: GeneraLized and COntextualized Story Explanations**Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, et al.*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2020-glucose-generalized-contextualized-story-explanations/)
29. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
30. **[GO FIGURE: A Meta Evaluation of Factuality in Summarization](https://md.research.elamur.ai/free/en/papers/gabriel-2021-go-figure-meta-evaluation-factuality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, et al.*2021 · 129 citations*
31. **[Improved Natural Language Generation via Loss Truncation](https://md.research.elamur.ai/free/en/papers/kang-2020-improved-natural-language-generation-loss/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Kang, Tatsunori B. Hashimoto*2020 · 129 citations*
32. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 117 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
33. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 113 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
34. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
35. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 110 citations*
36. **[Evaluating the Evaluation of Diversity in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/tevet-2021-evaluating-evaluation-diversity-natural-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Guy Tevet, Jonathan Berant*2021 · 103 citations*
37. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
38. **[Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation](https://md.research.elamur.ai/free/en/papers/deng-2021-compression-transduction-creation-unified-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingkai Deng, Bowen Tan, Zhengzhong Liu, et al.*2021 · 101 citations*
39. **[Truncation Sampling as Language Model Desmoothing](https://md.research.elamur.ai/free/en/papers/hewitt-2022-truncation-sampling-as-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**John Hewitt, Christopher Manning, Percy Liang*2022 · 92 citations*
40. [**GLM-5: from Vibe Coding to Agentic Engineering arXiv:2602.15763**Aohan Zeng, Xin Lv, Zhenyu Hou, et al.*2026 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-5-glm-5-vibe-coding/)
41. [**Small Language Models: Survey, Measurements, and Insights arXiv:2409.15790**Zhenyan Lu, Xiang Li, Dongqi Cai, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-small-language-models-survey-measurements/)
42. [**Trading Off Diversity and Quality in Natural Language Generation Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)**Hugh Zhang, Daniel Duckworth, Daphne Ippolito, et al.*2021 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-trading-off-diversity-quality-natural/)
43. **[Selectively Answering Ambiguous Questions](https://md.research.elamur.ai/free/en/papers/cole-2023-selectively-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jeremy Cole, Michael Zhang, Daniel Gillick, et al.*2023 · 78 citations*
44. [**LLMs Get Lost In Multi-Turn Conversation arXiv:2505.06120**Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.*2025 · 77 citations*](https://md.research.elamur.ai/free/en/papers/laban-2025-llms-get-lost-multi-turn/)
45. **[MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://md.research.elamur.ai/free/en/papers/xuan-2025-mmlu-prox-multilingual-benchmark-advanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Rui Yang, Heli Qi, et al.*2025 · 74 citations*
46. [**INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge arXiv:2411.19799**Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/romanou-2024-include-evaluating-multilingual-language-understanding/)
47. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 70 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)
48. [**Kimi K2.5: Visual Agentic Intelligence arXiv:2602.02276**Kimi Team, Tongtong Bai, Yifan Bai, et al.*2026 · 58 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2026-kimi-k2-5-visual/)
49. [**MiMo-V2-Flash Technical Report arXiv:2601.02780**Xiaomi LLM-Core Team; Bangjun Xiao; Bingquan Xia; Bo Yang; Bofei Gao; Bowen Shen; Chen Zhang; Chenhong He; Chiheng Lou; Fuli Luo; Gang Wang; Gang Xie; Hailin Zhang; Hanglong Lv; Hanyu Li; Heyu Chen; Hongshen Xu; Houbin Zhang; Huaqiu Liu; Jiangshan Duo; Jianyu Wei; Jiebao Xiao; Jinhao Dong; Jun Shi; Junhao Hu; Kainan Bao; Kang Zhou; Lei Li; Liang Zhao; Linghao Zhang; Peidian Li; Qianli Chen; Shaohui Liu; Shihua Yu; Shijie Cao; Shimao Chen; Shouqiu Yu; Shuo Liu; Tianling Zhou; Weijiang Su; Weikun Wang; Wenhan Ma; Xiangwei Deng; Bohan Mao; Bowen Ye; Can Cai; Chenghua Wang; Chengxuan Zhu; Chong Ma; Chun Chen; Chunan Li; Dawei Zhu; Deshan Xiao; Dong Zhang; Duo Zhang; Fangyue Liu; Feiyu Yang; Fengyuan Shi; Guoan Wang; Hao Tian; Hao Wu; Heng Qu; Hongfei Yi; Hongxu An; Hongyi Guan; Xing Zhang; Yifan Song; Yihan Yan; Yihao Zhao; Yingchun Lai; Yizhao Gao; Yu Cheng; Yuanyuan Tian; Yudong Wang; Zhen Tang; Zhengju Tang; Zhengtao Wen; Zhichao Song; Zhixian Zheng; Zihan Jiang; Jian Wen; Jiarui Sun; Jiawei Li; Jinlong Xue; Jun Xia; Kai Fang; Menghang Zhu; Nuo Chen; Qian Tu; Qihao Zhang; Qiying Wang; Rang Li; Rui Ma; Shaolei Zhang; Shengfan Wang; Shicheng Li; Shuhao Gu; Shuhuai Ren; Sirui Deng; Tao Guo; Tianyang Lu; Weiji Zhuang; Weikang Zhang; Weimin Xiong; Wenshan Huang; Wenyu Yang; Xin Zhang; Xing Yong; Xu Wang; Xueyang Xie; Yilin Jiang; Yixin Yang; Yongzhe He; Yu Tu; Yuanliang Dong; Yuchen Liu; Yue Ma; Yue Yu; Yuxing Xiang; Zhaojun Huang; Zhenru Lin; Zhipeng Xu; Zhiyang Chen; Zhonghua Deng; Zihan Zhang;, Zihao Yue*2026 · 58 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-llm-mimo-v2-flash-technical/)
50. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 58 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
51. **[Measuring the ‘I don't know' Problem through the Lens of Gricean Quantity](https://md.research.elamur.ai/free/en/papers/khayrallah-2021-measuring-i-don-t-know/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Huda Khayrallah, João Sedoc*2021 · 5 citations*
52. **[HistoriQA-ThirdRepublic: Multi-Hop Question Answering Corpus for Historical Research, Parliamentary Debates from the French Third Republic (1870-1940)](https://md.research.elamur.ai/free/en/papers/pellet-2026-historiqa-thirdrepublic-multi-hop-question/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aurelien Pellet, Marie Anna Puren, Julien PEREZ*2026 · 2 citations*
53. [**Adaptive Originality Filtering: Rejection Based Prompting and RiddleScore for Culturally Grounded Multilingual Riddle Generation arXiv:2508.18709**Duy Le, Kent Ziti, Evan Girard-Sun, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/le-2025-adaptive-originality-filtering-rejection-based/)
54. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

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

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