---
title: "Who cites Olga Golovneva — 271 papers of our library"
description: "271 papers of the Elamur Research library cite the works of Olga Golovneva, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/olga-golovneva/cited-by/"
---
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# Who cites Olga Golovneva

307 citations of their works from 271 papers of our library (of the 141,840 whose bibliographies we read) · 32 with a page here, the most cited first · [← Olga Golovneva](https://md.research.elamur.ai/free/en/authors/olga-golovneva/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
2. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,549 citations*
3. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 785 citations*
4. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 778 citations*
5. **[Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Miles Turpin, Julian Michael, Ethan Perez, et al.*2023 · 568 citations*
6. [**Large Language Models Cannot Self-Correct Reasoning Yet arXiv:2310.01798**Jie Huang, Xinyun Chen, Swaroop Mishra, et al.*2023 · 396 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/)
7. [**Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning arXiv:2305.12295**Liangming Pan, Alon Albalak, Xinyi Wang, et al.*2023 · 370 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)
8. **[Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters](https://md.research.elamur.ai/free/en/papers/wang-2023-understanding-chain-thought-prompting-empirical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boshi Wang, Sewon Min, Xiang Deng, et al.*2023 · 269 citations*
9. [**Prometheus: Inducing Fine-grained Evaluation Capability in Language Models arXiv:2310.08491**Seungone Kim, Jamin Shin, Yejin Cho, et al.*2023 · 267 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/)
10. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*
11. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
12. **[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 · 174 citations*
13. **[LLM-based NLG Evaluation: Current Status and Challenges](https://md.research.elamur.ai/free/en/papers/gao-2025-llm-based-nlg-evaluation-current/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Mingqi Gao, Xinyu Hu, Xunjian Yin, et al.*2025 · 152 citations*
14. [**REFINER: Reasoning Feedback on Intermediate Representations arXiv:2304.01904**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
15. **[Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework](https://md.research.elamur.ai/free/en/papers/zhao-2023-verify-edit-knowledge-enhanced-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Xingxuan Li, Shafiq Joty, et al.*2023 · 144 citations*
16. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
17. **[Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*
18. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
19. **[Deductive Verification of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*
20. **[Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Libo Qin, Qiguang Chen, Fuxuan Wei, et al.*2023 · 122 citations*
21. [**Generative Judge for Evaluating Alignment arXiv:2310.05470**Junlong Li, Shichao Sun, Weizhe Yuan, et al.*2023 · 121 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-generative-judge-evaluating-alignment/)
22. **[The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning](https://md.research.elamur.ai/free/en/papers/kim-2023-cot-collection-improving-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seungone Kim, Se Joo, Doyoung Kim, et al.*2023 · 116 citations*
23. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs arXiv:2410.18451**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 104 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
24. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
25. **[Evaluating Mathematical Reasoning Beyond Accuracy](https://md.research.elamur.ai/free/en/papers/xia-2024-evaluating-mathematical-reasoning-accuracy/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Shijie Xia, Xuefeng Li, Yixin Liu, et al.*2024 · 84 citations*
26. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
27. **[ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness](https://md.research.elamur.ai/free/en/papers/prasad-2023-receval-evaluating-reasoning-chains-correctness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Archiki Prasad, Swarnadeep Saha, Xiang Zhou, et al.*2023 · 68 citations*
28. [**Contrastive Decoding Improves Reasoning in Large Language Models arXiv:2309.09117**Sean O'Brien, Mike Lewis*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/o-brien-2023-contrastive-decoding-improves-reasoning-large/)
29. [**Inference-Time Scaling for Generalist Reward Modeling arXiv:2504.02495**Zijun Liu, Peiyi Wang, Runxin Xu, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-inference-time-scaling-generalist/)
30. [**Shepherd: A Critic for Language Model Generation arXiv:2308.04592**Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-shepherd-critic-language-model-generation/)
31. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
32. **[M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/feng-2025-m-mad-multidimensional-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaopeng Feng, Jiayuan Su, Jiamei Zheng, et al.*2025 · 24 citations*

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

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