---
title: "Who cites Reasoning Aware — 21 citing papers"
description: "21 papers of the Elamur Research library cite «Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling»…"
canonical: "https://research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reasoning Aware Self-Consistency: Leveraging…](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) / cited by

# Who cites «Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling»

21 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling»](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/)

1. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
2. [**Deep Think with Confidence arXiv:2508.15260**Yichao Fu, Xuewei Wang, Yuandong Tian, et al.*2025 · 61 citations*](https://md.research.elamur.ai/free/en/papers/fu-2025-deep-think-confidence/)
3. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/)
4. [**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/)
5. **[ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding](https://md.research.elamur.ai/free/en/papers/song-2026-thinkbrake-efficient-reasoning-log-probability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangjun Song, Minjae Oh, Seungkyu Lee, et al.*2026 · 1 citation*
6. **[Confidence-Weighted Token Set Cover for Early Hypothesis Pruning in Self-Consistency](https://md.research.elamur.ai/free/en/papers/sultan-2026-confidence-weighted-token-set-cover/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Arafat Sultan, Ramón Fernandez Astudillo*2026*
7. **[GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-grace-generative-approach-better-confidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2026*
8. **[Side-by-side Comparison Amplifies Dialect Bias in Language Models](https://md.research.elamur.ai/free/en/papers/kondapally-2026-side-side-comparison-amplifies-dialect/) [ACM Conference on Fairness, Accountability, and Transparency (FAccT)](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/)**Kritee Kondapally, Claire J. Smerdon, Pooja C. Patel, et al.*2026*
9. **[Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing](https://md.research.elamur.ai/free/en/papers/yuan-2026-verify-before-you-commit-faithful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Yuan, Chenchen Lin, Jian Chen, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) — Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling