---
title: "Who cites Jai Gupta"
description: "392 papers of the Elamur Research library cite the works of Jai Gupta, found in their bibliographies; the most cited first."
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# Who cites Jai Gupta

400 citations of their works from 392 papers of our library (of the 140,884 whose bibliographies we read) · 46 with a page here, the most cited first · [← Jai Gupta](https://md.research.elamur.ai/free/en/authors/jai-gupta/)

1. [**Training language models to follow instructions with human feedback**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 5,770 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
2. [**On the Opportunities and Risks of Foundation Models**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,044 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
3. [**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/)
4. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,215 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
5. [**Qwen Technical Report**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,643 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
6. [**Efficient Transformers: A Survey**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/)
7. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
8. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
9. [**WizardLM: Empowering large pre-trained language models to follow complex instructions**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 729 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/)
10. [**Crosslingual Generalization through Multitask Finetuning**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 692 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
11. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 590 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
12. [**Precise Zero-Shot Dense Retrieval without Relevance Labels**Luyu Gao, Xueguang Ma, Jimmy Lin, et al.*2022 · 545 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-precise-zero-shot-dense-retrieval/)
13. [**Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents**Weiwei Sun, Lingyong Yan, Xinyu Ma, et al.*2023 · 493 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-chatgpt-good-search-investigating-large/)
14. [**AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 423 citations*](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/)
15. [**UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 405 citations*](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/)
16. [**Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations**Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/)
17. [**BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/)
18. [**Large Language Models for Information Retrieval: A Survey**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/)
19. [**UL2: Unifying Language Learning Paradigms**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 334 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
20. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
21. [**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/)
22. [**Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting**Zhen Qin, Rolf Jagerman, Kai Hui, et al.*2024 · 296 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/)
23. [**A Holistic Approach to Undesired Content Detection in the Real World**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/)
24. [**LeanDojo: Theorem Proving with Retrieval-Augmented Language Models**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/)
25. [**DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/)
26. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 237 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
27. [**LawBench: Benchmarking Legal Knowledge of Large Language Models**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
28. [**Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models**Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.*2022 · 183 citations*](https://md.research.elamur.ai/free/en/papers/tirumala-2022-memorization-overfitting-analyzing-training-dynamics/)
29. [**Evaluating Large Language Models: A Comprehensive Survey**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
30. [**Lifting the Curse of Multilinguality by Pre-training Modular Transformers**Jonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.*2022 · 172 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2022-lifting-curse-multilinguality-pre-training/)
31. [**Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/)
32. [**WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/)
33. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
34. [**SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/)
35. [**ExpertQA: Expert-Curated Questions and Attributed Answers**Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/malaviya-2024-expertqa-expert-curated-questions-attributed/)
36. [**Tokenizer Choice For LLM Training: Negligible or Crucial?**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/)
37. [**Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP**Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.*2021 · 89 citations*](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/)
38. [**The SIGMORPHON 2022 Shared Task on Morpheme Segmentation**Khuyagbaatar Batsuren, Gabor Bella, Aryaman Arora*2022 · 71 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-morpheme-segmentation/)
39. [**Evaluating Various Tokenizers for Arabic Text Classification**Zaid Alyafeai, Maged S. Al-shaibani, Mustafa Ghaleb, et al.*2021 · 66 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2021-evaluating-various-tokenizers-arabic-text/)
40. [**Transcending Scaling Laws with 0.1% Extra Compute**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
41. [**Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew**Eylon Gueta, Omer Goldman, Reut Tsarfaty*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/gueta-2023-explicit-morphological-knowledge-improves-pre/)
42. [**Pragmatic Inference Chain (PIC) Improving LLMs' Reasoning of Authentic Implicit Toxic Language**Xi Chen, Shuo Wang*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pragmatic-inference-chain-pic-improving/)
43. [**Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models**Mohamed Taher Alrefaie, Nour Eldin Morsy, Nada Samir*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/alrefaie-2024-exploring-tokenization-strategies-vocabulary-sizes/)
44. [**KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models**Wajdi Zaghouani, Shimaa Amer Ibrahim, Aruzhan Muratbek, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-kz-safetyprompts-kazakh-safety-evaluation/)
45. [**HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*2026*](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/)
46. [**The Impact of Tokenization Algorithms on Hungarian Language Model Performance**Mátyás Osváth, Máté Norbert Molnár, Roland Gunics, et al.*2026*](https://md.research.elamur.ai/free/en/papers/osvath-2026-impact-tokenization-algorithms-hungarian-language/)

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

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