---
title: "Who cites Bryan Kian Hsiang Low — 97 papers of our library"
description: "97 papers of the Elamur Research library cite the works of Bryan Kian Hsiang Low, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/bryan-kian-hsiang-low/cited-by/"
---
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# Who cites Bryan Kian Hsiang Low

97 citations of their works from 97 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← Bryan Kian Hsiang Low](https://md.research.elamur.ai/free/en/authors/bryan-kian-hsiang-low/)

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 · 2,875 citations*
2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
3. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
4. **[Large Language Models Are Zero-Shot Time Series Forecasters](https://md.research.elamur.ai/free/en/papers/gruver-2023-large-language-models-zero-shot/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nate Gruver, Marc Finzi, Shikai Qiu, et al.*2023 · 268 citations*
5. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
6. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
7. [**Stable LM 2 1.6B Technical Report arXiv:2402.17834**Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/bellagente-2024-stable-lm-2-1-6b/)
8. **[ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability](https://md.research.elamur.ai/free/en/papers/liu-2026-reasonrank-empowering-passage-ranking-strong/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhan Liu, Xinyu Ma, Weiwei Sun, et al.*2026 · 18 citations*
9. **[RaDeR: Reasoning-aware Dense Retrieval Models](https://md.research.elamur.ai/free/en/papers/das-2025-rader-reasoning-aware-dense-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Debrup Das, Sam O'Nuallain, Razieh Rahimi*2025 · 14 citations*
10. **[Alignment for Efficient Tool Calling of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-alignment-efficient-tool-calling-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongshen Xu, Zihan Wang, Zichen Zhu, et al.*2025 · 13 citations*
11. **[DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers](https://md.research.elamur.ai/free/en/papers/ma-2025-drama-diverse-augmentation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Xi Victoria Lin, Barlas Oguz, et al.*2025 · 13 citations*
12. **[Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2025-diffusion-vs-autoregressive-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siyue Zhang, Yilun Zhao, Liyuan Geng, et al.*2025 · 10 citations*
13. [**Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic arXiv:2412.04277**Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-arabic-stable-lm-adapting-stable/)
14. **[Test-time Corpus Feedback: From Retrieval to RAG](https://md.research.elamur.ai/free/en/papers/rathee-2026-test-time-corpus-feedback-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mandeep Rathee, Venktesh V, Sean MacAvaney, et al.*2026 · 4 citations*
15. **[Query Decomposition for RAG: Balancing Exploration-Exploitation](https://md.research.elamur.ai/free/en/papers/petcu-2026-query-decomposition-rag-balancing-exploration/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Roxana Petcu, Kenton Murray, Daniel Khashabi, et al.*2026 · 2 citations*
16. **[What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search](https://md.research.elamur.ai/free/en/papers/zhang-2026-what-makes-llm-good-optimizer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinhao Zhang, Xi Chen, François Portet, et al.*2026 · 1 citation*
17. **[A Survey of Reasoning-Intensive Retrieval: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/wei-2026-survey-reasoning-intensive-retrieval-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyang Wei, Tingyu Song, Siyue Zhang, et al.*2026*
18. **[Let Retrievers Think Before Action: Thought-Augmented Embedding for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/yan-2026-let-retrievers-think-before-action/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruiran Yan, Wen Xiong, Ze Liu, et al.*2026*
19. **[PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models](https://md.research.elamur.ai/free/en/papers/ouyang-2026-pyramathbench-evaluating-improving-mathematical-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zetian Ouyang, Linlin Wang, Gerard de Melo, et al.*2026*
20. **[RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2026-rag-wild-effectiveness-llms-mixture/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ran Xu, Yuchen Zhuang, Yue Yu, et al.*2026*
21. **[Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems](https://md.research.elamur.ai/free/en/papers/zhao-2026-rethinking-reasoning-intensive-retrieval-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Jinbiao Wei, Tingyu Song, et al.*2026*

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

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