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Who cites Brandon Norick

1,600 citations of their works from 1,521 papers of our library (of the 149,439 whose bibliographies we read) · 335 with a page here, the most cited first · page 1 of 4 · 1–100 · ← Brandon Norick

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  1. LLaMA: Open and Efficient Foundation Language ModelsarXiv:2302.13971Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 9,603 citations
  2. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  3. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  4. Large language models are zero-shot reasonersConference on Neural Information Processing Systems (NeurIPS)Takeshi Kojima, Shixiang Shane Gu, Machel Reid, et al.2022 · 3,832 citations
  5. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  6. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  7. Training Compute-Optimal Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, et al.2022 · 2,032 citations
  8. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  9. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  10. MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language ModelsarXiv:2304.10592Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.2023 · 1,141 citations
  11. LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.2024 · 1,048 citations
  12. Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
  13. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
  14. Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Conference on Empirical Methods in Natural Language Processing (EMNLP)Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.2023 · 828 citations
  15. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  16. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  17. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations
  18. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  19. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesFindings of the Association for Computational LinguisticsCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023 · 690 citations
  20. Atlas: Few-shot Learning with Retrieval Augmented Language ModelsarXiv:2208.03299Gautier Izacard, Patrick Lewis, Maria Lomeli, et al.2022 · 673 citations
  21. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  22. Phi-4 Technical ReportarXiv:2412.08905Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.2024 · 502 citations
  23. Orca: A Distributed Serving System for Transformer-Based Generative ModelsOSDI 2022Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, et al.2022 · 478 citations
  24. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  25. GPT-NER: Named Entity Recognition via Large Language ModelsFindings of the Association for Computational LinguisticsShuhe Wang, Xiaofei Sun, Xiaoya Li, et al.2025 · 436 citations
  26. The FineWeb Datasets: Decanting the Web for the Finest Text Data at ScaleConference on Neural Information Processing Systems (NeurIPS)Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.2024 · 434 citations
  27. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  28. FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precisionConference on Neural Information Processing Systems (NeurIPS)Jay Shah, Ganesh Bikshandi, Ying Zhang, et al.2024 · 400 citations
  29. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 400 citations
  30. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
  31. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  32. Language Is Not All You Need: Aligning Perception with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Shaohan Huang, Li Dong, Wenhui Wang, et al.2023 · 330 citations
  33. ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale TransformersConference on Neural Information Processing Systems (NeurIPS)Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.2022 · 304 citations
  34. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  35. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  36. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
  37. Reducing Activation Recomputation in Large Transformer ModelsarXiv:2205.05198Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.2022 · 273 citations
  38. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
  39. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
  40. QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMsConference on Neural Information Processing Systems (NeurIPS)Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.2024 · 254 citations
  41. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
  42. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  43. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
  44. SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and VerificationACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.2023 · 220 citations
  45. Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
  46. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
  47. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  48. MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse AttentionConference on Neural Information Processing Systems (NeurIPS)Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.2024 · 202 citations
  49. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  50. MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
  51. Improving Passage Retrieval with Zero-Shot Question GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Devendra Sachan, Mike Lewis, Mandar Joshi, et al.2022 · 199 citations
  52. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  53. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 190 citations
  54. Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
  55. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  56. Thinking about GPT-3 In-Context Learning for Biomedical IE? Think AgainFindings of the Association for Computational LinguisticsBernal Jimenez Gutierrez, Nikolas McNeal, Clayton Washington, et al.2022 · 180 citations
  57. Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved YetConference on Machine Translation (WMT)Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.2024 · 178 citations
  58. Scaling Synthetic Data Creation with 1,000,000,000 PersonasarXiv:2406.20094Tao Ge, Xin Chan, Xiaoyang Wang, et al.2024 · 171 citations
  59. SqueezeLLM: Dense-and-Sparse QuantizationarXiv:2306.07629Sehoon Kim, Coleman Hooper, Amir Gholami, et al.2023 · 170 citations
  60. Factuality Enhanced Language Models for Open-Ended Text GenerationConference on Neural Information Processing Systems (NeurIPS)Nayeon Lee, Wei Ping, Peng Xu, et al.2022 · 168 citations
  61. GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation ModelsarXiv:2508.06471Aohan Zeng, Xin Lv, Qinkai Zheng, et al.2025 · 166 citations
  62. LongVideoBench: A Benchmark for Long-context Interleaved Video-Language UnderstandingConference on Neural Information Processing Systems (NeurIPS)Haoning Wu, Dongxu Li, Bei Chen, et al.2024 · 166 citations
  63. DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer ModelsarXiv:2309.14509Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al.2023 · 162 citations
  64. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  65. Large Language Models with Controllable Working MemoryFindings of the Association for Computational LinguisticsDaliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.2023 · 158 citations
  66. MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUsarXiv:2402.15627Ziheng Jiang, Haibin Lin, Yinmin Zhong, et al.2024 · 157 citations
  67. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  68. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
  69. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 150 citations
  70. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  71. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
  72. A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence GenerationarXiv:2307.03987Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu2023 · 143 citations
  73. Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and FaithfulnessarXiv:2304.11633Bo Li, Gexiang Fang, Yang Yang, et al.2023 · 142 citations
  74. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  75. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 137 citations
  76. AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.2022 · 135 citations
  77. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  78. Scaling Up Models and Data with t5x and seqioarXiv:2203.17189Adam Roberts, Hyung Won Chung, Anselm Levskaya, et al.2022 · 130 citations
  79. You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual SettingsBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsZeerak Talat, Aurélie Névéol, Stella Biderman, et al.2022 · 130 citations
  80. Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base ModelConference on Neural Information Processing Systems (NeurIPS)Jingcheng Hu, Yinmin Zhang, Qi Han, et al.2025 · 128 citations
  81. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
  82. MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding BenchmarkarXiv:2409.02813Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.2024 · 123 citations
  83. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
  84. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksarXiv:2404.02151Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion2024 · 118 citations
  85. Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 114 citations
  86. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  87. Efficient Large Scale Language Modeling with Mixtures of ExpertsarXiv:2112.10684Mikel Artetxe, Shruti Bhosale, Naman Goyal, et al.2021 · 113 citations
  88. Efficient Large Language Models: A SurveyarXiv:2312.03863Zhongwei Wan, Xin Wang, Che Liu, et al.2023 · 110 citations
  89. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
  90. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
  91. PolyLM: An Open Source Polyglot Large Language ModelarXiv:2307.06018Xiangpeng Wei, Haoran Wei, Huan Lin, et al.2023 · 103 citations
  92. LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language ModelsInternational Conference on Learning Representations (ICLR)Gunho Park, Baeseong Park, Minsub Kim, et al.2022 · 103 citations
  93. A Careful Examination of Large Language Model Performance on Grade School ArithmeticConference on Neural Information Processing Systems (NeurIPS)Hugh Zhang, Jeff Da, Dean Lee, et al.2024 · 101 citations
  94. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
  95. LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive MemoryarXiv:2410.10813Di Wu, Hongwei Wang, Wenhao Yu, et al.2024 · 95 citations
  96. LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 93 citations
  97. How well do Large Language Models perform in Arithmetic tasks?arXiv:2304.02015Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 93 citations
  98. Small Language Models are the Future of Agentic AIarXiv:2506.02153Peter Belcak, Greg Heinrich, Shizhe Diao, et al.2025 · 92 citations
  99. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
  100. BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-HaystackConference on Neural Information Processing Systems (NeurIPS)Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.2024 · 88 citations

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