---
title: "Who cites Akshay Krishnamurthy — 108 papers of our library"
description: "108 papers of the Elamur Research library cite the works of Akshay Krishnamurthy, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/akshay-krishnamurthy/cited-by/"
---
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# Who cites Akshay Krishnamurthy

108 citations of their works from 108 papers of our library (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← Akshay Krishnamurthy](https://md.research.elamur.ai/free/en/authors/akshay-krishnamurthy/)

1. **[The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning](https://md.research.elamur.ai/free/en/papers/agarwal-2025-unreasonable-effectiveness-entropy-minimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivam Agarwal, Zimin Zhang, Lifan Yuan, et al.*2025 · 47 citations*
2. [**Learning to Reason without External Rewards arXiv:2505.19590**Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-learning-reason-external-rewards/)
3. [**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/)
4. **[From Selection to Generation: A Survey of LLM-based Active Learning](https://md.research.elamur.ai/free/en/papers/xia-2025-selection-generation-survey-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, et al.*2025 · 22 citations*
5. [**Can Large Reasoning Models Self-Train? arXiv:2505.21444**Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/)
6. [**Weight Ensembling Improves Reasoning in Language Models arXiv:2504.10478 · COLM 2025**Xingyu Dang, Christina Baek, Kaiyue Wen, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/dang-2025-weight-ensembling-improves-reasoning-language/)
7. [**PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier arXiv:2506.10406**Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-pag-multi-turn-reinforced-llm/)
8. **[Imbalanced Gradients in RL Post-Training of Multi-Task LLMs](https://md.research.elamur.ai/free/en/papers/wu-2026-imbalanced-gradients-rl-post-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Runzhe Wu, Ankur Samanta, Ayush Jain, et al.*2026 · 3 citations*
9. **[Active Generalized Category Discovery with Diverse LLM Feedback](https://md.research.elamur.ai/free/en/papers/zou-2026-active-generalized-category-discovery-diverse/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Henry Peng Zou, Siffi Singh, Yi Nian, et al.*2026 · 1 citation*
10. **[LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific Tasks](https://md.research.elamur.ai/free/en/papers/lu-2026-llms-now-fine-tuning-later/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Lu, Bingsheng Yao, Shao Zhang, et al.*2026*

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

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