---
title: "Who cites Gabriel Grand — 75 papers of our library"
description: "75 papers of the Elamur Research library cite the works of Gabriel Grand, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/gabriel-grand/cited-by/"
---
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# Who cites Gabriel Grand

75 citations of their works from 75 papers of our library (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · [← Gabriel Grand](https://md.research.elamur.ai/free/en/authors/gabriel-grand/)

1. **[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 · 608 citations*
2. **[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 · 176 citations*
3. [**From System 1 to System 2: A Survey of Reasoning Large Language Models arXiv:2502.17419**Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.*2025 · 165 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-system-1-system-2-survey/)
4. **[Prompting is not a substitute for probability measurements in large language models](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jennifer Hu, Roger Levy*2023 · 133 citations*
5. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
6. [**HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs arXiv:2412.18925**Junying Chen, Zhenyang Cai, Ke Ji, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-huatuogpt-o1-towards-medical-complex/)
7. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
8. **[Recursive Introspection: Teaching Language Model Agents How to Self-Improve](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.*2024 · 75 citations*
9. **[Training Language Models to Reason Efficiently](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Daman Arora, Andrea Zanette*2025 · 74 citations*
10. [**Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents arXiv:2408.07199**Pranav Putta, Edmund Mills, Naman Garg, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/putta-2024-agent-q-advanced-reasoning-learning/)
11. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
12. [**DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning arXiv:2504.07128**Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/)
13. [**Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought arXiv:2501.04682**Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2025-towards-system-2-reasoning-llms/)
14. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
15. [**Evaluating Language Models for Mathematics through Interactions arXiv:2306.01694**Katherine M. Collins, Albert Q. Jiang, Simon Frieder, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/collins-2023-evaluating-language-models-mathematics-through/)
16. [**Scaling Test-Time Compute Without Verification or RL is Suboptimal arXiv:2502.12118**Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2025-scaling-test-time-compute-verification/)
17. [**Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning arXiv:2506.06632**Shubham Parashar, Shurui Gui, Xiner Li, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/parashar-2025-curriculum-reinforcement-learning-easy-hard/)
18. **[Do Large Language Models Understand Conversational Implicature- A case study with a Chinese sitcom](https://md.research.elamur.ai/free/en/papers/yue-2024-do-large-language-models-understand/) [Chinese National Conference on Computational Linguistics](https://md.research.elamur.ai/free/en/venues/ccl/)**Shisen Yue, Siyuan Song, Xinyuan Cheng, et al.*2024 · 19 citations*
19. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/)
20. **[Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference Tuning](https://md.research.elamur.ai/free/en/papers/wu-2024-rethinking-pragmatics-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shengguang Wu, Shusheng Yang, Zhenglun Chen, et al.*2024 · 16 citations*
21. [**Mastering Board Games by External and Internal Planning with Language Models arXiv:2412.12119**John Schultz, Jakub Adamek, Matej Jusup, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/schultz-2024-mastering-board-games-external-internal/)
22. **[Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2026-meta-reasoner-dynamic-guidance-optimized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Sui, Yufei He, Tri Cao, et al.*2026 · 13 citations*
23. [**Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search arXiv:2502.02508**Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/)
24. [**EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration arXiv:2410.06238**Allen Nie, Yi Su, Bo Chang, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/nie-2024-evolve-evaluating-optimizing-llms-context/)
25. [**Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models arXiv:2405.15143**Cong Lu, Shengran Hu, Jeff Clune*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-intelligent-go-explore-standing-shoulders/)
26. [**Comparing human and LLM politeness strategies in free production**Haoran Zhao, Robert D. Hawkins*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-comparing-human-llm-politeness-strategies/)
27. [**Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation arXiv:2502.01694**Juno Kim, Denny Wu, Jason Lee, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-metastable-dynamics-chain-thought-reasoning/)
28. [**BoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery arXiv:2501.01540**Kanishk Gandhi, Michael Y. Li, Lyle Goodyear, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-boxinggym-benchmarking-progress-automated/)
29. **[Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference](https://md.research.elamur.ai/free/en/papers/yuan-2026-quantifying-impact-structured-output-format/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Yuan, Yue Zhao, Li Zhang, et al.*2026 · 2 citations*
30. [**Pragmatics beyond humans: meaning, communication, and LLMs arXiv:2508.06167**Vit Gvoždiak*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gvo-vzdiak-2025-pragmatics-humans-meaning-communication-llms/)
31. [**Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering**Polina Tsvilodub, Robert D. Hawkins, Michael Franke*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2025-integrating-neural-symbolic-components-model/)
32. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026*
33. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
34. **[POLAR: A Corpus of Questions, Responses and Argumentation in Polish Political Radio Discourse](https://md.research.elamur.ai/free/en/papers/ziembicki-2026-polar-corpus-questions-responses-argumentation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daniel Ziembicki, Aleksandra Zwierzchowska, Ewelina Sobol, et al.*2026*

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

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