--- title: "Who cites Daniel Fu" description: "564 papers of the Elamur Research library cite the works of Daniel Fu, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/daniel-fu/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/daniel-fu/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Daniel Fu](https://md.research.elamur.ai/free/en/authors/daniel-fu/) / cited by # Who cites Daniel Fu 568 citations of their works from 564 papers of our library (of the 140,884 whose bibliographies we read) · 21 with a page here, the most cited first · [← Daniel Fu](https://md.research.elamur.ai/free/en/authors/daniel-fu/) 1. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) 2. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) 3. [**SGLang: Efficient Execution of Structured Language Model Programs**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 710 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) 4. [**Yi: Open Foundation Models by 01.AI**Alex Young, Bei Chen, Chao Li, et al.*2024 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/) 5. [**TinyLlama: An Open-Source Small Language Model**Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.*2024 · 350 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-tinyllama-open-source-small-language/) 6. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/) 7. [**KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization**Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al.*2024 · 293 citations*](https://md.research.elamur.ai/free/en/papers/hooper-2024-kvquant-towards-10-million-context/) 8. [**LLM-QAT: Data-Free Quantization Aware Training for Large Language Models**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 275 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/) 9. [**QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 252 citations*](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/) 10. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache**Zirui Liu, Jiayi Yuan, Hongye Jin, et al.*2024 · 243 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/) 11. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/) 12. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/) 13. [**LLM in a flash: Efficient Large Language Model Inference with Limited Memory**Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.*2024 · 192 citations*](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/) 14. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 160 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/) 15. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) 16. [**Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**Jun Zhang, Jue Wang, Huan Li, et al.*2024 · 146 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-draft-verify-lossless-large-language/) 17. [**EuroLLM: Multilingual Language Models for Europe**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/) 18. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/) 19. [**MAmmoTH2: Scaling Instructions from the Web**Xiang Yue, Tuney Zheng, Ge Zhang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mammoth2-scaling-instructions-web/) 20. [**New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) 21. [**In-Distribution Steering: Balancing Control and Coherence in Language Model Generation**Arthur Vogels, Benjamin Wong, Yann Choho, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/vogels-2026-distribution-steering-balancing-control-coherence/) 543 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/daniel-fu/) — Daniel Fu