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title: "Andrew Lampinen · Google — author profile and papers"
description: "Andrew Lampinen, Google: 2 papers on Elamur Research (2022–2024), h-index 17 — affiliations, topics, co-authors and who cites them in…"
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# Andrew Lampinen

Andrew Lampinen has 2 papers in our library, in 2022–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Antonia Creswell](https://md.research.elamur.ai/free/en/authors/antonia-creswell/), [Felix Hill](https://md.research.elamur.ai/free/en/authors/felix-hill/), [Stephanie Chan](https://md.research.elamur.ai/free/en/authors/stephanie-chan/).

2 papers in our library · 2022–2024

[OpenAlex](https://openalex.org/A5030015839) · [ORCID](https://orcid.org/0000-0002-6988-8437) · [Wikidata](https://www.wikidata.org/wiki/Q104281913) · [**h-index 17**](https://openalex.org/authors/A5030015839) · [67 works](https://openalex.org/works?filter=author.id:A5030015839) · [1,528 citations](https://openalex.org/works?filter=author.id:A5030015839&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/andrew-lampinen/#papers) · [🔗 Cited 1,659 times in our library](https://md.research.elamur.ai/free/en/authors/andrew-lampinen/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #4592](https://md.research.elamur.ai/free/en/paper-stars/page/46/#star-4592)

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=Andrew+Lampinen) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Andrew+Lampinen) · [dblp](https://dblp.org/search?q=Andrew+Lampinen) · [ACL Anthology](https://aclanthology.org/search/?q=Andrew+Lampinen)

## Affiliations

[🏢**Google DeepMind** London · United Kingdom 2021–2026 · 16 papers*current*](https://md.research.elamur.ai/free/en/companies/google-deepmind/) · [🏢**Google** Mountain View · United States 2024–2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/companies/google/) · [🏢**Anthropic** San Francisco · United States 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/anthropic/) · [🎓**Stanford University** Stanford · United States 2017–2025 · 18 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**École Polytechnique Fédérale de Lausanne** Lausanne · Switzerland 2025 · 2 papers](https://md.research.elamur.ai/free/en/universities/ecole-polytechnique-federale-de-lausanne/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed.

## 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 · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 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 · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/andrew-lampinen/year/2024/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/andrew-lampinen/year/2022/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/)** *(2022 · 295 citations)* Large language models can pick up new tasks from a handful of in-context examples. The authors test whether adding explanations to those examples, as people do when teaching, also helps models. They took 40 difficult tasks and subtasks from BIG-bench. For each, one author wrote post-answer explanations for 15 sampled…
2. **[Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and Humans](https://md.research.elamur.ai/free/en/papers/lampinen-2024-can-language-models-handle-recursively/)** *(2024 · 63 citations)* Earlier work (Lakretz et al. 2021, 2022) suggested that Transformer LMs handle recursively center-embedded sentences worse than people do. On the hardest subject-verb agreement condition, models scored at or below chance. This paper argues that the comparison was unbalanced. Human participants received instructions…

## All works

7 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
2. **[Language models show human-like content effects on reasoning tasks ↗](https://arxiv.org/abs/2207.07051) arXiv:2207.07051 · no summary yet**Ishita Dasgupta et al.*2022 · 162 citations*
3. **[Data Distributional Properties Drive Emergent In-Context Learning in Transformers ↗](https://arxiv.org/abs/2205.05055) arXiv:2205.05055 · no summary yet**Stephanie C. Y. Chan et al.*2022 · 158 citations*
4. **[Symbol tuning improves in-context learning in language models ↗](https://aclanthology.org/2023.emnlp-main.61/) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yet**Jerry Wei et al.*2023 · 68 citations*
5. **[Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and Humans](https://md.research.elamur.ai/free/en/papers/lampinen-2024-can-language-models-handle-recursively/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Andrew Lampinen*2024 · 63 citations*
6. **[Interpretability Illusions in the Generalization of Simplified Models ↗](https://arxiv.org/abs/2312.03656) arXiv (Cornell University) · no summary yet**Dan Friedman et al.*2023 · 9 citations*
7. **[Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention ↗](https://arxiv.org/abs/2605.29548) arXiv (Cornell University) · no summary yet**Jing Huang et al.*2026*

## Co-authors here

3 co-authors with a page, the most papers together first.

- [Antonia Creswell](https://md.research.elamur.ai/free/en/authors/antonia-creswell/)
- [Felix Hill](https://md.research.elamur.ai/free/en/authors/felix-hill/)
- [Stephanie Chan](https://md.research.elamur.ai/free/en/authors/stephanie-chan/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/): [Computational Linguistics 2024](https://md.research.elamur.ai/free/en/venues/cl/2024/)
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2022](https://md.research.elamur.ai/free/en/venues/findings/2022/)
- Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

## Cited by

Papers of our library cite their works 1,659 times (of the 149,439 papers whose bibliographies we read); [368 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/andrew-lampinen/cited-by/).

Updated 30 October 2026
