---
title: "Who cites Han Guo — 206 papers of our library"
description: "206 papers of the Elamur Research library cite the works of Han Guo, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/han-guo/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/han-guo/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Han Guo](https://md.research.elamur.ai/free/en/authors/han-guo/) / cited by

# Who cites Han Guo

206 citations of their works from 206 papers of our library (of the 149,439 whose bibliographies we read) · 46 with a page here, the most cited first · [← Han Guo](https://md.research.elamur.ai/free/en/authors/han-guo/)

1. **[DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-r1-incentivizing-reasoning-capability/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**DeepSeek-AI, Daya Guo, Dejian Yang, et al.*2025 · 4,728 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. [**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/)
4. [**Large Language Models as Optimizers arXiv:2309.03409**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 413 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/)
5. **[Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reid Pryzant, Dan Iter, Jerry Li, et al.*2023 · 409 citations*
6. [**Demystifying Prompts in Language Models via Perplexity Estimation arXiv:2212.04037**Hila Gonen, Srini Iyer, Terra Blevins, et al.*2022 · 213 citations*](https://md.research.elamur.ai/free/en/papers/gonen-2022-demystifying-prompts-language-models-perplexity/)
7. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
8. **[Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering](https://md.research.elamur.ai/free/en/papers/wu-2022-self-adaptive-context-learning-information/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, et al.*2022 · 159 citations*
9. **[Fine-Tuning Language Models with Just Forward Passes](https://md.research.elamur.ai/free/en/papers/malladi-2023-fine-tuning-language-models-just/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sadhika Malladi, Tianyu Gao, Eshaan Nichani, et al.*2023 · 153 citations*
10. **[Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery](https://md.research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Wen, Neel Jain, John Kirchenbauer, et al.*2023 · 141 citations*
11. [**EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers arXiv:2309.08532**Qingyan Guo, Rui Wang, Junliang Guo, et al.*2023 · 111 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evoprompt-connecting-llms-evolutionary-algorithms/)
12. [**PaperQA: Retrieval-Augmented Generative Agent for Scientific Research arXiv:2312.07559**Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/)
13. [**PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization arXiv:2310.16427**Xinyuan Wang, Chenxi Li, Zhen Wang, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-promptagent-strategic-planning-language-models/)
14. **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 99 citations*
15. [**Language Agents as Optimizable Graphs arXiv:2402.16823**Mingchen Zhuge, Wenyi Wang, Louis Kirsch, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/zhuge-2024-language-agents-optimizable-graphs/)
16. **[RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs](https://md.research.elamur.ai/free/en/papers/akyurek-2023-rl4f-generating-natural-language-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.*2023 · 89 citations*
17. [**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/)
18. [**On Prompt-Driven Safeguarding for Large Language Models arXiv:2401.18018**Chujie Zheng, Fan Yin, Hao Zhou, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-prompt-driven-safeguarding-large-language/)
19. **[Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering](https://md.research.elamur.ai/free/en/papers/liu-2022-rainier-reinforced-knowledge-introspector-commonsense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiacheng Liu, Skyler Hallinan, Ximing Lu, et al.*2022 · 82 citations*
20. **[TTRL: Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zuo-2025-ttrl-test-time-reinforcement-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.*2025 · 76 citations*
21. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
22. [**Explore, Establish, Exploit: Red Teaming Language Models from Scratch arXiv:2306.09442**Stephen Casper, Jason Lin, Joe Kwon, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/casper-2023-explore-establish-exploit-red-teaming/)
23. [**Parameter-Efficient Fine-Tuning Design Spaces arXiv:2301.01821**Jiaao Chen, Aston Zhang, Xingjian Shi, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/)
24. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations*
25. **[Knowledge Boundary of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/li-2025-knowledge-boundary-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moxin Li, Yong Zhao, Wenxuan Zhang, et al.*2025 · 30 citations*
26. **[Aristotle: IMO-level Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/achim-2025-aristotle-imo-level-automated-theorem/) [SuperIntelligence - Robotics - Safety & Alignment](https://md.research.elamur.ai/free/en/venues/superintelligence-robotics-safety-alignment/)**Tudor Achim, Alex Best, Alberto Bietti, et al.*2025 · 29 citations*
27. **[Joint Prompt Optimization of Stacked LLMs using Variational Inference](https://md.research.elamur.ai/free/en/papers/sordoni-2023-joint-prompt-optimization-stacked-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.*2023 · 23 citations*
28. [**Rethinking Reflection in Pre-Training arXiv:2504.04022**Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shah-2025-rethinking-reflection-pre-training/)
29. [**Training a Scientific Reasoning Model for Chemistry arXiv:2506.17238**Siddharth M. Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/narayanan-2025-training-scientific-reasoning-model/)
30. **[Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering](https://md.research.elamur.ai/free/en/papers/jurayj-2025-is-that-your-final-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Jurayj, Jeffrey Cheng, Benjamin Van Durme*2025 · 11 citations*
31. [**AMR-TST: Abstract Meaning Representation-based Text Style Transfer**Kaize Shi, Xueyao Sun, Li He, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-amr-tst-abstract-meaning-representation/)
32. [**T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation**Anubhav Jangra, Preksha Nema, Aravindan Raghuveer*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/jangra-2022-t-star-truthful-style-transfer/)
33. **[Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs](https://md.research.elamur.ai/free/en/papers/li-2025-self-instructed-derived-prompt-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuo Li, Yuhao Du, Jinpeng Hu, et al.*2025 · 9 citations*
34. [**Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement arXiv:2505.07961**Xuechen Zhang, Zijian Huang, Chenshun Ni, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-making-small-language-models-efficient/)
35. **[Detecting Training Data of Large Language Models via Expectation Maximization](https://md.research.elamur.ai/free/en/papers/kim-2026-detecting-training-data-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gyuwan Kim, Yang Li, Evangelia Spiliopoulou, et al.*2026 · 5 citations*
36. **[Gated Differentiable Working Memory for Long-Context Language Modeling](https://md.research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
37. **[Query Decomposition for RAG: Balancing Exploration-Exploitation](https://md.research.elamur.ai/free/en/papers/petcu-2026-query-decomposition-rag-balancing-exploration/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Roxana Petcu, Kenton Murray, Daniel Khashabi, et al.*2026 · 2 citations*
38. **[Diff4TST: Masked Diffusion Language Model for Text Style Transfer](https://md.research.elamur.ai/free/en/papers/ma-2026-diff4tst-masked-diffusion-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinchen Ma, Gaole He, Yunshi Lan, et al.*2026*
39. **[Gradient-Guided Multi-Judge Prompt Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-gradient-guided-multi-judge-prompt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ChenZhuo Zhao, Xinda Wang, Pu Zhao, et al.*2026*
40. **[Joint Optimization of Training Data and Policy in RLHF](https://md.research.elamur.ai/free/en/papers/yu-2026-joint-optimization-training-data-policy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohao Yu, Jiali Zeng, Weizheng Gu, et al.*2026*
41. **[Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reference-attack-new-cross-modal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Yifei Fu, Jiayi Gao*2026*
42. **[Test-Time Training for Zero-Resource Dense Retrieval Reranking](https://md.research.elamur.ai/free/en/papers/liu-2026-test-time-training-zero-resource/) [Workshop on Towards Knowledgeable Foundation Models](https://md.research.elamur.ai/free/en/venues/knowfm/)**Shiyan Liu, Yichen Li*2026*
43. **[Thesis Proposal: Toward a Human-Centered and Perspective-Aware Framework for Reproducible ML Evaluation and AI Alignment](https://md.research.elamur.ai/free/en/papers/pandita-2026-thesis-proposal-human-centered-perspective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deepak Pandita, Christopher M. Homan*2026*
44. **[Think Earlier, Not Longer: Prompt Optimization via Reducing Unhealthy Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-think-earlier-not-longer-prompt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ling-I Wu, Minyu Chen, Jingyang Li, et al.*2026*
45. **[To Write or to Automate Linguistic Prompts, That Is the Question](https://md.research.elamur.ai/free/en/papers/torron-2026-write-or-automate-linguistic-prompts/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Marina Sánchez-Torrón, Daria Akselrod, Jason Rauchwerk*2026*
46. **[Your Reasoning Benchmark May Not Test Reasoning: Revealing Perception Bottleneck in Abstract Reasoning Benchmarks](https://md.research.elamur.ai/free/en/papers/wang-2026-your-reasoning-benchmark-may-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinhe Wang, Jin Huang, Xingjian Zhang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/han-guo/) — Han Guo