--- title: "Who cites Don't throw away your value — 44 citing papers" description: "44 papers of the Elamur Research library cite «Don't throw away your value model! Generating more preferable text with Value-Guided…" canonical: "https://research.elamur.ai/free/en/papers/liu-2023-don-t-throw-away-value/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/liu-2023-don-t-throw-away-value/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Don't throw away your value model! Generating…](https://md.research.elamur.ai/free/en/papers/liu-2023-don-t-throw-away-value/) / cited by # Who cites «Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding» 44 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding»](https://md.research.elamur.ai/free/en/papers/liu-2023-don-t-throw-away-value/) 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. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models arXiv:2408.00724**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/) 4. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations* 5. [**From r to Q*: Your Language Model is Secretly a Q-Function arXiv:2404.12358**Rafael Rafailov, Joey Hejna, Ryan Park, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/rafailov-2024-r-q-language-model-secretly/) 6. [**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/) 7. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations* 8. **[Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2024-weak-strong-search-align-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhanhui Zhou, Zhixuan Liu, Jie Liu, et al.*2024 · 17 citations* 9. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/) 10. **[VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search](https://md.research.elamur.ai/free/en/papers/wang-2025-visuothink-empowering-lvlm-reasoning-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yikun Wang, Siyin Wang, Qinyuan Cheng, et al.*2025 · 13 citations* 11. **[Progressive Multimodal Reasoning via Active Retrieval](https://md.research.elamur.ai/free/en/papers/dong-2025-progressive-multimodal-reasoning-active-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.*2025 · 10 citations* 12. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026* 32 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/liu-2023-don-t-throw-away-value/) — Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding