--- title: "Eliza Rutherford — author profile and papers" description: "Eliza Rutherford: 2 papers on Elamur Research (2022), h-index 9 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/eliza-rutherford/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/eliza-rutherford/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Eliza Rutherford # Eliza Rutherford Eliza Rutherford's papers here concern large neural networks trained on vast amounts of text and images, within the areas of [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/) and [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/). Two questions run through the work. How should a limited training budget be divided between model size and data? And can a single model take on new visual tasks from a handful of examples rather than through task-specific fine-tuning? The most cited of these papers is [Flamingo: a Visual Language Model for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/). It presents a family of models that read images and video together with text and produce free-form language. Shown only a few demonstrations in the prompt, they can adapt to new tasks. The second paper, [Training Compute-Optimal Large Language Models](https://md.research.elamur.ai/free/en/papers/hoffmann-2022-training-compute-optimal-large-language/), trains a large set of transformer language models across many sizes and data quantities. From these runs, it estimates in several independent ways how parameters and training tokens should grow together for a fixed amount of compute. The answer is that both should rise in step. By that measure, many large language models of the period were oversized and given too little training text. Both papers date from 2022, so they also mark the most recent direction here: a move from studying how language models scale toward combining language with vision. The work was done in large collaborative teams. [Arthur Mensch](https://md.research.elamur.ai/free/en/authors/arthur-mensch/) appears as a co-author on both papers. Other collaborators include [Jean-Baptiste Alayrac](https://md.research.elamur.ai/free/en/authors/jean-baptiste-alayrac/), [Sebastian Borgeaud](https://md.research.elamur.ai/free/en/authors/sebastian-borgeaud/) and [Lisa Anne Hendricks](https://md.research.elamur.ai/free/en/authors/lisa-anne-hendricks/). Eliza Rutherford has 2 papers in our library, in 2022, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Arthur Mensch](https://md.research.elamur.ai/free/en/authors/arthur-mensch/), [Aidan Clark](https://md.research.elamur.ai/free/en/authors/aidan-clark/), [Jean-Baptiste Alayrac](https://md.research.elamur.ai/free/en/authors/jean-baptiste-alayrac/). 2 papers in our library · 2022 [OpenAlex](https://openalex.org/A5042672461) · [**h-index 9**](https://openalex.org/authors/A5042672461) · [9 works](https://openalex.org/works?filter=author.id:A5042672461) · [4,607 citations](https://openalex.org/works?filter=author.id:A5042672461&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/eliza-rutherford/#papers) · [🔗 5,346 citations in our library](https://md.research.elamur.ai/free/en/authors/eliza-rutherford/cited-by/) · [⭐ Paper Star rank #797](https://md.research.elamur.ai/free/en/paper-stars/page/8/#star-797) 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=Eliza+Rutherford) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Eliza+Rutherford) · [dblp](https://dblp.org/search?q=Eliza+Rutherford) · [ACL Anthology](https://aclanthology.org/search/?q=Eliza+Rutherford) ## Topics [Language models & pretraining (2)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language (1)](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2022** 2 papers](https://md.research.elamur.ai/free/en/authors/eliza-rutherford/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[Flamingo: a Visual Language Model for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)** *(2022 · 2,108 citations)* Most vision systems still need thousands of labelled examples and careful fine-tuning for each new task. Contrastive image–text models avoid fine-tuning, but they only score text–image similarity and cannot generate free-form language. This DeepMind paper introduces Flamingo, a family of Visual Language Models (3B… 2. **[Training Compute-Optimal Large Language Models](https://md.research.elamur.ai/free/en/papers/hoffmann-2022-training-compute-optimal-large-language/)** *(2022 · 1,110 citations)* The authors from DeepMind investigate how best to split a fixed compute budget (FLOPs) between two things: the size of a transformer language model and the number of tokens it is trained on. ## Co-authors here 10 co-authors with a page, the most papers together first. - [Arthur Mensch](https://md.research.elamur.ai/free/en/authors/arthur-mensch/) ×2 - [Aidan Clark](https://md.research.elamur.ai/free/en/authors/aidan-clark/) - [Jean-Baptiste Alayrac](https://md.research.elamur.ai/free/en/authors/jean-baptiste-alayrac/) - [Jeff Donahue](https://md.research.elamur.ai/free/en/authors/jeff-donahue/) - [Johannes Welbl](https://md.research.elamur.ai/free/en/authors/johannes-welbl/) - [Katie Millican](https://md.research.elamur.ai/free/en/authors/katie-millican/) - [Lisa Anne Hendricks](https://md.research.elamur.ai/free/en/authors/lisa-anne-hendricks/) - [Roman Ring](https://md.research.elamur.ai/free/en/authors/roman-ring/) - [Sebastian Borgeaud](https://md.research.elamur.ai/free/en/authors/sebastian-borgeaud/) - [Trevor Cai](https://md.research.elamur.ai/free/en/authors/trevor-cai/) ## Cited by Papers of our library cite their works 5,346 times (of the 140,884 papers whose bibliographies we read); [351 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/eliza-rutherford/cited-by/).