---
title: "Who cites The Good, The Bad, and The — 38 citing papers"
description: "38 papers of the Elamur Research library cite «The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore…"
canonical: "https://research.elamur.ai/free/en/papers/song-2025-good-bad-greedy-evaluation-llms/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/song-2025-good-bad-greedy-evaluation-llms/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [The Good, The Bad, and The Greedy: Evaluation of…](https://md.research.elamur.ai/free/en/papers/song-2025-good-bad-greedy-evaluation-llms/) / cited by

# Who cites «The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism»

38 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism»](https://md.research.elamur.ai/free/en/papers/song-2025-good-bad-greedy-evaluation-llms/)

1. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
2. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
3. **[When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/khairi-2025-when-life-gives-you-samples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ammar Khairi, Daniel D'souza, Ye Shen, et al.*2025 · 6 citations*
4. **[ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers](https://md.research.elamur.ai/free/en/papers/sengupta-2026-tooldreamer-instilling-llm-reasoning-into/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Saptarshi Sengupta, Zhengyu Zhou, Jun Araki, et al.*2026 · 1 citation*
5. **[Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-refine-self-refinement-parallel/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qibin Wang, Pu Zhao, Shaohan Huang, et al.*2026*
6. **[On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-temperature-constrained-non-deterministic-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weichuan Wang, Mingyang Liu, Chen Ma, et al.*2026*
7. **[Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics](https://md.research.elamur.ai/free/en/papers/tran-2026-program-structure-aware-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Khang Tran, Khoa Nguyen, Cristian Borcea, et al.*2026*

31 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/song-2025-good-bad-greedy-evaluation-llms/) — The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism