---
title: "Who cites Nishant Subramani"
description: "368 papers of the Elamur Research library cite the works of Nishant Subramani, found in their bibliographies; the most cited first."
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---
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# Who cites Nishant Subramani

369 citations of their works from 368 papers of our library (of the 140,884 whose bibliographies we read) · 42 with a page here, the most cited first · [← Nishant Subramani](https://md.research.elamur.ai/free/en/authors/nishant-subramani/)

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. [**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. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,695 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
4. [**PaLM 2 Technical Report**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 971 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
5. [**GPT-NeoX-20B: An Open-Source Autoregressive Language Model**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 818 citations*](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/)
6. [**Inference-Time Intervention: Eliciting Truthful Answers from a Language Model**Kenneth Li, Oam Patel, Fernanda Viegas, et al.*2023 · 473 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-inference-time-intervention-eliciting-truthful/)
7. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
8. [**Ethical and social risks of harm from Language Models**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 421 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
9. [**Editing Models with Task Arithmetic**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 374 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
10. [**Datasets: A Community Library for Natural Language Processing**Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, et al.*2021 · 358 citations*](https://md.research.elamur.ai/free/en/papers/lhoest-2021-datasets-community-library-natural-language/)
11. [**Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages**Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, et al.*2022 · 307 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2022-samanantar-largest-publicly-available-parallel/)
12. [**The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 259 citations*](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/)
13. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
14. [**NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 245 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/)
15. [**In-context Examples Selection for Machine Translation**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/)
16. [**Steering Language Models With Activation Engineering**Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/turner-2023-steering-language-models-activation-engineering/)
17. [**MADLAD-400: A Multilingual And Document-Level Large Audited Dataset**Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/kudugunta-2023-madlad-400-multilingual-document-level/)
18. [**mGPT: Few-Shot Learners Go Multilingual**Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.*2022 · 203 citations*](https://md.research.elamur.ai/free/en/papers/shliazhko-2022-mgpt-few-shot-learners-go/)
19. [**Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 202 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/)
20. [**AraT5: Text-to-Text Transformers for Arabic Language Generation**El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed*2022 · 201 citations*](https://md.research.elamur.ai/free/en/papers/nagoudi-2022-arat5-text-text-transformers-arabic/)
21. [**IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages**Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.*2023 · 200 citations*](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/)
22. [**Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/)
23. [**CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages**Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.*2023 · 179 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-culturax-cleaned-enormous-multilingual-dataset/)
24. [**Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages**Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/doddapaneni-2023-leaving-no-indic-language-behind/)
25. [**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/)
26. [**A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation**David Ifeoluwa Adelani, Jesujoba Oluwadara Alabi, Angela Fan, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2022-few-thousand-translations-go-long/)
27. [**Towards a Cleaner Document-Oriented Multilingual Crawled Corpus**Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, et al.*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/abadji-2022-towards-cleaner-document-oriented-multilingual/)
28. [**Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation**Nuno M. Guerreiro, Elena Voita, André Martins*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-looking-needle-haystack-comprehensive-study/)
29. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
30. [**Extracting Latent Steering Vectors from Pretrained Language Models**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/)
31. [**GlotLID: Language Identification for Low-Resource Languages**Amir Hossein Kargaran, Ayyoob Imani, François Yvon, et al.*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/kargaran-2023-glotlid-language-identification-low-resource/)
32. [**An Open Dataset and Model for Language Identification**Laurie Burchell, Alexandra Birch, Nikolay Bogoychev, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/burchell-2023-open-dataset-model-language-identification/)
33. [**TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages**Anirudh Srinivasan, Eunsol Choi*2022 · 29 citations*](https://md.research.elamur.ai/free/en/papers/srinivasan-2022-tydip-dataset-politeness-classification-nine/)
34. [**An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)**Laurie Burchell, Ona de Gibert, Nikolay Arefyev, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/burchell-2025-expanded-massive-multilingual-dataset-high/)
35. [**Alignment at Pre-training! Towards Native Alignment for Arabic LLMs**Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/liang-2024-alignment-pre-training-towards-native/)
36. [**Evaluating Machine Translation Datasets for Low-Web Data Languages: A Gendered Lens**Hellina Hailu Nigatu, Bethelhem Yemane Mamo, Bontu Fufa Balcha, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nigatu-2026-evaluating-machine-translation-datasets-low/)
37. [**Analysis of Data Augmentation Methods for Low-Resource Maltese ASR**Andrea DeMarco; Carlos Mena; Albert Gatt; Claudia Borg; Aiden Williams;, Lonneke van der Plas*2021 · 1 citation*](https://md.research.elamur.ai/free/en/papers/demarco-2021-analysis-data-augmentation-methods-low/)
38. [**Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026*](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/)
39. [**ParaCLEAN: Improving Translation Quality through Systematic Parallel Data Cleaning**Audrey Mash, Ella Paulina Bohman, Maite Melero*2026*](https://md.research.elamur.ai/free/en/papers/mash-2026-paraclean-improving-translation-quality-through/)
40. [**Quality and Appropriateness of Large Text Datasets for Irish NLP**Abigail Walsh, Mark Andrade, Jane Lauren Adkins, et al.*2026*](https://md.research.elamur.ai/free/en/papers/walsh-2026-quality-appropriateness-large-text-datasets/)
41. [**SemiAdapt: Semi-Supervised and Efficient LoRA-Based Domain Adaptation for Low-Resource Irish Machine Translation with Transformers**Josh Mcgiff, Nikola S. Nikolov*2026*](https://md.research.elamur.ai/free/en/papers/mcgiff-2026-semiadapt-semi-supervised-efficient-lora/)
42. [**Variation Is the Norm: Embracing Sociolinguistics in NLP**Anne-Marie Lutgen, Alistair Plum, Verena Blaschke, et al.*2026*](https://md.research.elamur.ai/free/en/papers/lutgen-2026-variation-is-norm-embracing-sociolinguistics/)

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

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