🧑‍🔬 Who cites Yang Yang

184 citations of their works from 184 papers of our library (of the 140,884 whose bibliographies we read) · 35 with a page here, the most cited first · ← Yang Yang

1. Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 10,782 citations
2. Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,295 citations
3. Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerColin Raffel, Noam Shazeer, Adam Roberts, et al.2019 · 7,433 citations
4. LLaMA: Open and Efficient Foundation Language ModelsHugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 5,609 citations
5. On the Opportunities and Risks of Foundation ModelsRishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,044 citations
6. Scaling Laws for Neural Language ModelsJared Kaplan, Sam McCandlish, Tom Henighan, et al.2020 · 1,814 citations
7. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,695 citations
8. Reproducible scaling laws for contrastive language-image learningMehdi Cherti, Romain Beaumont, Ross Wightman, et al.2022 · 750 citations
9. Massively Multilingual Neural Machine Translation in the Wild: Findings and ChallengesNaveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.2019 · 555 citations
10. Instruction Tuning for Large Language Models: A SurveyShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 515 citations
11. GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsNan Du, Yanping Huang, Andrew M. Dai, et al.2021 · 474 citations
12. The Falcon Series of Open Language ModelsEbtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 436 citations
13. Are Emergent Abilities of Large Language Models a Mirage?Rylan Schaeffer, Brando Miranda, Sanmi Koyejo2023 · 323 citations
14. Challenges and Applications of Large Language ModelsJean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 300 citations
15. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 297 citations
16. NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each BenchmarkOscar Sainz, Jon Campos, Iker García-Ferrero, et al.2023 · 245 citations
17. Large Language Monkeys: Scaling Inference Compute with Repeated SamplingBradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.2024 · 241 citations
18. Beyond neural scaling laws: beating power law scaling via data pruningBen Sorscher, Robert Geirhos, Shashank Shekhar, et al.2022 · 220 citations
19. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 198 citations
20. SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and ArabicIbrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, et al.2022 · 146 citations
21. The case for 4-bit precision: k-bit Inference Scaling LawsTim Dettmers, Luke Zettlemoyer2022 · 119 citations
22. Scaling Laws for Autoregressive Generative ModelingTom Henighan, Jared Kaplan, Mor Katz, et al.2020 · 115 citations
23. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsYangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 114 citations
24. Scaling Laws for TransferDanny Hernandez, Jared Kaplan, Tom Henighan, et al.2021 · 102 citations
25. SemDeDup: Data-efficient learning at web-scale through semantic deduplicationAmro Abbas, Kushal Tirumala, Dániel Simig, et al.2023 · 94 citations
26. Scaling Laws and Interpretability of Learning from Repeated DataDanny Hernandez, Tom Brown, Tom Conerly, et al.2022 · 62 citations
27. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsNikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 47 citations
28. Scaling Laws for Generative Mixed-Modal Language ModelsArmen Aghajanyan, Lili Yu, Alexis Conneau, et al.2023 · 39 citations
29. Observational Scaling Laws and the Predictability of Language Model PerformanceYangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 28 citations
30. The Quantization Model of Neural ScalingEric J. Michaud, Ziming Liu, Uzay Girit, et al.2023 · 27 citations
31. Distillation Scaling LawsDan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 23 citations
32. Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language ModelsQingkai Min, Qipeng Guo, Xiangkun Hu, et al.2024 · 19 citations
33. Resolving Discrepancies in Compute-Optimal Scaling of Language ModelsTomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.2024 · 14 citations
34. Sarcasm Detection is Way Too Easy! An Empirical Comparison of Human and Machine Sarcasm DetectionIbrahim Abu Farha, Steven Wilson, Silviu Oprea, et al.2022 · 13 citations
35. Contrastively Pre-trained Event Embeddings with Schema-free LLM AnnotationsFrank Mtumbuka, Steven Schockaert2026

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