--- title: "Brian Lester — author profile and papers — Elamur Research" description: "Brian Lester: 3 papers on Elamur Research (2021–2022) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/brian-lester/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/brian-lester/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Brian Lester # Brian Lester Brian Lester has 3 papers in our library, in 2021–2022, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Noah Constant](https://md.research.elamur.ai/free/en/authors/noah-constant/), [Rami Al-Rfou](https://md.research.elamur.ai/free/en/authors/rami-al-rfou/), [Adams Wei Yu](https://md.research.elamur.ai/free/en/authors/adams-wei-yu/). 3 papers in our library · 2021–2022 No OpenAlex profile matched yet. [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/brian-lester/#papers) · [🔗 Cited 3,395 times in our library](https://md.research.elamur.ai/free/en/authors/brian-lester/cited-by/) · [⭐ Paper Stars ranking: #511](https://md.research.elamur.ai/free/en/paper-stars/page/6/#star-511) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Brian+Lester) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Brian+Lester) · [dblp](https://dblp.org/search?q=Brian+Lester) · [ACL Anthology](https://aclanthology.org/search/?q=Brian+Lester) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) 💡 Concepts 2 Key ideas and methods explained on our concept pages.[Fine-tuning · 1 work](https://md.research.elamur.ai/free/en/concepts/fine-tuning/) · [Few-shot learning · 1 work](https://md.research.elamur.ai/free/en/concepts/few-shot-learning/) ## Works by year ### 2020s [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/brian-lester/year/2022/) · [**2021** 2 papers](https://md.research.elamur.ai/free/en/authors/brian-lester/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[The Power of Scale for Parameter-Efficient Prompt Tuning](https://md.research.elamur.ai/free/en/papers/lester-2021-power-scale-parameter-efficient-prompt/)** *(2021 · 4,287 citations)* The paper examines how to adapt a large pretrained language model to specific tasks without changing its weights. 2. **[Finetuned Language Models Are Zero-Shot Learners](https://md.research.elamur.ai/free/en/papers/wei-2021-finetuned-language-models-zero-shot/)** *(2021 · 1,954 citations)* Large language models such as GPT-3 perform well when the prompt contains a few examples. Without examples, that is, in the zero-shot setting, their quality drops noticeably. The authors from Google Research propose instruction tuning: a pretrained model is fine-tuned on a mixture of tasks, each formulated as an… 3. **[SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/)** *(2022 · 306 citations)* Prompt tuning adapts a frozen pre-trained model by learning only a short sequence of soft prompt tokens for each task. ## Co-authors here 12 co-authors with a page, the most papers together first. - [Noah Constant](https://md.research.elamur.ai/free/en/authors/noah-constant/) ×2 - [Rami Al-Rfou](https://md.research.elamur.ai/free/en/authors/rami-al-rfou/) ×2 - [Adams Wei Yu](https://md.research.elamur.ai/free/en/authors/adams-wei-yu/) - [Andrew M. Dai](https://md.research.elamur.ai/free/en/authors/andrew-m-dai/) - [Daniel Cer](https://md.research.elamur.ai/free/en/authors/daniel-cer/) - [Jason Wei](https://md.research.elamur.ai/free/en/authors/jason-wei/) - [Kelvin Guu](https://md.research.elamur.ai/free/en/authors/kelvin-guu/) - [Maarten Bosma](https://md.research.elamur.ai/free/en/authors/maarten-bosma/) - [Nan Du](https://md.research.elamur.ai/free/en/authors/nan-du/) - [Quoc Viet Le](https://md.research.elamur.ai/free/en/authors/quoc-viet-le/) - [Tu Vu](https://md.research.elamur.ai/free/en/authors/tu-vu/) - [Vincent Zhao](https://md.research.elamur.ai/free/en/authors/vincent-zhao/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2022](https://md.research.elamur.ai/free/en/venues/acl/2022/) - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2021](https://md.research.elamur.ai/free/en/venues/emnlp/2021/) ## Cited by Papers of our library cite their works 3,395 times (of the 149,439 papers whose bibliographies we read); [577 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/brian-lester/cited-by/). Updated 30 October 2026