--- title: "Who cites Elena Simperl" description: "204 papers of the Elamur Research library cite the works of Elena Simperl, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/elena-simperl/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/elena-simperl/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Elena Simperl](https://md.research.elamur.ai/free/en/authors/elena-simperl/) / cited by # Who cites Elena Simperl 204 citations of their works from 204 papers of our library (of the 140,884 whose bibliographies we read) · 23 with a page here, the most cited first · [← Elena Simperl](https://md.research.elamur.ai/free/en/authors/elena-simperl/) 1. [**Language Models as Knowledge Bases?**Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.*2019 · 2,977 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2019-language-models-as-knowledge-bases/) 2. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,879 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/) 3. [**Retrieval-Augmented Generation for Large Language Models: A Survey**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,647 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) 4. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/) 5. [**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/) 6. [**KILT: a Benchmark for Knowledge Intensive Language Tasks**Fabio Petroni, Aleksandra Piktus, Angela Fan, et al.*2020 · 663 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-kilt-benchmark-knowledge-intensive-language/) 7. [**K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters**Ruize Wang, Duyu Tang, Nan Duan, et al.*2020 · 662 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/) 8. [**Learning How to Ask: Querying LMs with Mixtures of Soft Prompts**Guanghui Qin, Jason Eisner*2021 · 566 citations*](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/) 9. [**Few-shot Learning with Multilingual Language Models**Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/lin-2021-few-shot-learning-multilingual-language/) 10. [**Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly**Nora Kassner, Hinrich Schütze*2020 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2020-negated-misprimed-probes-pretrained-language/) 11. [**Factual Probing Is MASK: Learning vs. Learning to Recall**Zexuan Zhong, Dan Friedman, Danqi Chen*2021 · 411 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2021-factual-probing-is-mask-learning/) 12. [**Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/) 13. [**How Context Affects Language Models' Factual Predictions**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 231 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/) 14. [**Re2G: Retrieve, Rerank, Generate**Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.*2022 · 183 citations*](https://md.research.elamur.ai/free/en/papers/glass-2022-re2g-retrieve-rerank-generate/) 15. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) 16. [**Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models**Nora Kassner, Philipp Dufter, Hinrich Schütze*2021 · 175 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2021-multilingual-lama-investigating-knowledge-multilingual/) 17. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/) 18. [**Simple Entity-Centric Questions Challenge Dense Retrievers**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) 19. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/) 20. [**Large Language Models with Controllable Working Memory**Daliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-controllable-working/) 21. [**DART: Open-Domain Structured Data Record to Text Generation**Linyong Nan, Dragomir Radev, Rui Zhang, et al.*2020 · 154 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/) 22. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/) 23. [**Contrastively Pre-trained Event Embeddings with Schema-free LLM Annotations**Frank Mtumbuka, Steven Schockaert*2026*](https://md.research.elamur.ai/free/en/papers/mtumbuka-2026-contrastively-pre-trained-event-embeddings/) 181 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/elena-simperl/) — Elena Simperl