---
title: "Who cites A New Generation of Perspective — 86 citing papers"
description: "86 papers of the Elamur Research library cite «A New Generation of Perspective API: Efficient Multilingual Character-level Transformers»…"
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# Who cites «A New Generation of Perspective API: Efficient Multilingual Character-level Transformers»

86 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «A New Generation of Perspective API: Efficient Multilingual Character-level Transformers»](https://md.research.elamur.ai/free/en/papers/lees-2022-new-generation-perspective-api/)

1. [**Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations arXiv:2312.06674**Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.*2023 · 395 citations*](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/)
2. **[BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 362 citations*
3. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
4. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 347 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
5. **[A Holistic Approach to Undesired Content Detection in the Real World](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 263 citations*
6. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
7. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
8. **[WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 165 citations*
9. **[Language Model Behavior: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/chang-2024-language-model-behavior-comprehensive-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tyler A. Chang, Benjamin K. Bergen*2024 · 148 citations*
10. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 119 citations*
11. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
12. **[AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails](https://md.research.elamur.ai/free/en/papers/ghosh-2025-aegis2-0-diverse-ai-safety/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shaona Ghosh, Prasoon Varshney, Makesh Narsimhan Sreedhar, et al.*2025 · 53 citations*
13. [**Lost in Translation: Large Language Models in Non-English Content Analysis arXiv:2306.07377**Gabriel Nicholas, Aliya Bhatia*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/nicholas-2023-lost-translation-large-language-models/)
14. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
15. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
16. **[Pragmatic Inference Chain (PIC) Improving LLMs' Reasoning of Authentic Implicit Toxic Language](https://md.research.elamur.ai/free/en/papers/chen-2025-pragmatic-inference-chain-pic-improving/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xi Chen, Shuo Wang*2025 · 9 citations*
17. **[KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-kz-safetyprompts-kazakh-safety-evaluation/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Wajdi Zaghouani, Shimaa Amer Ibrahim, Aruzhan Muratbek, et al.*2026 · 2 citations*
18. **[Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework](https://md.research.elamur.ai/free/en/papers/weng-2026-safe-sail-fine-grained-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Weng, Han Zheng, Hanyu Zhang, et al.*2026 · 2 citations*
19. **[HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*2026*
20. **[Modeling Linguistic Violence: An Ontology-Based Framework for the Computational Analysis of Violence Manifested in Language](https://md.research.elamur.ai/free/en/papers/santana-2026-modeling-linguistic-violence-ontology-based/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Brenda Salenave Santana, Ana Marilza Pernas, Aline A. Vanin*2026*
21. **[RLShield: Dynamic Jailbreak Detection for LLMs via Reinforced Adaptive Learning](https://md.research.elamur.ai/free/en/papers/tong-2026-rlshield-dynamic-jailbreak-detection-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhao Tong, Pengfei Yang, Yimeng Gu, et al.*2026*

65 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/lees-2022-new-generation-perspective-api/) — A New Generation of Perspective API: Efficient Multilingual Character-level Transformers
