---
title: "Who cites Rethinking with Retrieval: Faithful — 96 citing papers"
description: "96 papers of the Elamur Research library cite «Rethinking with Retrieval: Faithful Large Language Model Inference», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Rethinking with Retrieval: Faithful Large…](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/) / cited by

# Who cites «Rethinking with Retrieval: Faithful Large Language Model Inference»

96 papers of our library cite it (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · [← back to «Rethinking with Retrieval: Faithful Large Language Model Inference»](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
2. **[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 · 780 citations*
3. **[Benchmarking Large Language Models in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chen-2023-benchmarking-large-language-models-retrieval/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jiawei Chen, Hongyu Lin, Xianpei Han, et al.*2023 · 629 citations*
4. **[Enabling Large Language Models to Generate Text with Citations](https://md.research.elamur.ai/free/en/papers/gao-2023-enabling-large-language-models-generate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyu Gao, Howard Yen, Jiatong Yu, et al.*2023 · 485 citations*
5. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
6. [**Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback arXiv:2302.12813**Baolin Peng, Michel Galley, Pengcheng He, et al.*2023 · 363 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-check-facts-try-again-improving/)
7. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations*
8. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
9. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
10. [**Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness arXiv:2304.11633**Bo Li, Gexiang Fang, Yang Yang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-chatgpt-s-information-extraction/)
11. **[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*
12. **[Self-Knowledge Guided Retrieval Augmentation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-self-knowledge-guided-retrieval-augmentation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yile Wang, Peng Li, Maosong Sun, et al.*2023 · 135 citations*
13. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
14. **[ExpertQA: Expert-Curated Questions and Attributed Answers](https://md.research.elamur.ai/free/en/papers/malaviya-2024-expertqa-expert-curated-questions-attributed/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.*2024 · 113 citations*
15. **[Answering Questions by Meta-Reasoning over Multiple Chains of Thought](https://md.research.elamur.ai/free/en/papers/yoran-2023-answering-questions-meta-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Tomer Wolfson, Ben Bogin, et al.*2023 · 99 citations*
16. **[Boosting Language Models Reasoning with Chain-of-Knowledge Prompting](https://md.research.elamur.ai/free/en/papers/wang-2024-boosting-language-models-reasoning-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianing Wang, Qiushi Sun, Xiang Li, et al.*2024 · 94 citations*
17. [**Improving Language Models via Plug-and-Play Retrieval Feedback arXiv:2305.14002**Wenhao Yu, Zhihan Zhang, Zhenwen Liang, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-improving-language-models-plug-play/)
18. **[“According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data](https://md.research.elamur.ai/free/en/papers/weller-2024-according-prompting-language-models-improves/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Orion Weller, Marc Marone, Nathaniel Weir, et al.*2024 · 46 citations*
19. [**PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions arXiv:2305.14908**Anthony Chen, Panupong Pasupat, Sameer Singh, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-purr-efficiently-editing-language-model/)
20. [**Large Language Models are Strong Zero-Shot Retriever arXiv:2304.14233**Tao Shen, Guodong Long, Xiubo Geng, et al.*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-models-strong-zero/)
21. **[TC–RAG: Turing–Complete RAG's Case study on Medical LLM Systems](https://md.research.elamur.ai/free/en/papers/jiang-2025-tc-rag-turing-complete-rag/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinke Jiang, Yue Fang, Rihong Qiu, et al.*2025 · 25 citations*
22. **[HALoGEN: Fantastic LLM Hallucinations and Where to Find Them](https://md.research.elamur.ai/free/en/papers/ravichander-2025-halogen-fantastic-llm-hallucinations-where/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abhilasha Ravichander, Shrusti Ghela, David Wadden, et al.*2025 · 22 citations*
23. [**Source-Aware Training Enables Knowledge Attribution in Language Models arXiv:2404.01019**Muhammad Khalifa, David Wadden, Emma Strubell, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/khalifa-2024-source-aware-training-enables-knowledge/)
24. **[Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study Over Open-ended Question Answering](https://md.research.elamur.ai/free/en/papers/sui-2025-can-knowledge-graphs-make-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Sui, Yufei He, Zifeng Ding, et al.*2025 · 16 citations*
25. **[Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers](https://md.research.elamur.ai/free/en/papers/xu-2025-can-llms-identify-critical-limitations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijian Xu, Yilun Zhao, Manasi Patwardhan, et al.*2025 · 11 citations*
26. **[HiChunk: Evaluating and Enhancing Retrieval Augmented Generation with Hierarchical Chunking](https://md.research.elamur.ai/free/en/papers/lu-2026-hichunk-evaluating-enhancing-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wensheng Lu, Keyu Chen, Zhifeng Shen, et al.*2026 · 4 citations*
27. **[DRAGON: Domain-specific Robust Automatic Data Generation for RAG Optimization](https://md.research.elamur.ai/free/en/papers/shen-2026-dragon-domain-specific-robust-automatic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Shen, Hang Yan, Zhongshi Xing, et al.*2026 · 1 citation*
28. **[R^3AG: Retriever Routing for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhao-2026-r-textasciicircum3ag-retriever-routing-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tong Zhao, Yutao Zhu, Yucheng Tian, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/) — Rethinking with Retrieval: Faithful Large Language Model Inference
