🧑‍🔬 Who cites Arjun Subramonian

176 citations of their works from 168 papers of our library (of the 141,840 whose bibliographies we read) · 23 with a page here, the most cited first · ← Arjun Subramonian

1. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,680 citations
2. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,703 citations
3. A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the UglyarXiv:2312.02003Yifan Yao, Jinhao Duan, Kaidi Xu, et al.2023 · 1,182 citations
4. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 977 citations
5. 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 · 821 citations
6. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 779 citations
7. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 592 citations
8. Having Beer after Prayer? Measuring Cultural Bias in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tarek Naous, Michael J. Ryan, Alan Ritter, et al.2023 · 268 citations
9. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 246 citations
10. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 245 citations
11. Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 164 citations
12. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 147 citations
13. 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
14. ArabicMMLU: Assessing Massive Multitask Language Understanding in ArabicFindings of the Association for Computational LinguisticsFajri Koto, Haonan Li, Sara Shatnawi, et al.2024 · 116 citations
15. BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.2023 · 101 citations
16. Inseq: An Interpretability Toolkit for Sequence Generation ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Gabriele Sarti, Nils Feldhus, Ludwig Sickert, et al.2023 · 96 citations
17. NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 88 citations
18. Recognition of They/Them as Singular Personal Pronouns in Coreference ResolutionConnor Baumler, Rachel Rudinger2022 · 19 citations
19. Gender Bias Evaluation in Machine Translation for Amharic, Tigrigna, and Afaan OromooWorkshop on Gender-Inclusive Translation TechnologiesWalelign Sewunetie, Atnafu Tonja, Tadesse Belay, et al.2024 · 5 citations
20. Adapting Psycholinguistic Research for LLMs: Gender-inclusive Language in a Coreference ContextWorkshop on Gender Bias in Natural Language ProcessingMarion Bartl, Thomas Brendan Murphy, Susan Leavy2025 · 3 citations
21. Evaluating Machine Translation Datasets for Low-Web Data Languages: A Gendered LensFindings of the Association for Computational LinguisticsHellina Hailu Nigatu, Bethelhem Yemane Mamo, Bontu Fufa Balcha, et al.2026 · 1 citation
22. How Far Can Bias Go? Tracing Bias from Pre-Training Data to AlignmentLanguage Resources and Evaluation Conference (LREC)Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.2026
23. Yeswa-Stories: A Three-Way Parallel Dataset of Female African Figures in Low-Web Data LanguagesWorkshop on Gender-Inclusive Translation TechnologiesBethelhem Mamo, Hellina Nigatu2026

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