Researcher
Rylan Schaeffer
Current role not listed
Schaeffer studies how the tests we use shape what we think AI can do. In a NeurIPS paper, he and his co-authors showed that some abilities that seem to appear suddenly as language models grow can look like gradual improvements when scored differently.[1]
Career & education
Previously
Meta2025-Jul 2026AI Research Scientist
Google DeepMind2024-2025Research Scientist, Gemini Pretraining & Data
Uber2018-2019Data Scientist
Meta2025-Jul 2026Google DeepMind2024-2025Uber2018-2019
Stanford University
Harvard University
UCL
UC DavisWork and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations10,521As of Nov 12, '26
Updates 1
References
- Are Emergent Abilities of Large Language Models a Mirage?arxiv.org
The paper tests how scoring choices can make smooth improvements look like sudden jumps in ability.
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Reviewed August 15, 2026 · Checked for accuracy and new information.