Advancing the frontier of AI and scientific discovery in finance.
Explore research, publications and open-source contributions from Capital One's scientists and engineers.
Latest publications
Large databases need small, open-weight language models
Key system optimizations required to efficiently deploy open-weight models within an LM-DB system.
QDBO: A real-time quantum-augmented database system optimizer
A white-box quantum-augmented database optimizer that directly leverages low-level quantum sampling on a quantum annealer.
Learning to route queries to heads for attention-based re-ranking with large language models
A query-dependent head selection method for attention-based re-ranking with LLMs.
What do safety-aligned LLMs learn from mixed compliance demonstrations?
A Hypothesis-Testing Study of Mixed Many-Shot Contexts.
EPSVec: Efficient and private synthetic data generation via dataset vectors
A differentially-private lightweight alternative that steers LLM generation using dataset vectors.
Ask, don’t judge: Binary questions for interpretable LLM evaluation and self-improvement
A framework that decomposes evaluation criteria into atomic binary questions and aggregates the resulting verdicts.
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Latest blogs
Latest blogs
Highlights from MLSys 2026
Capital One’s AI research team recaps MLSys 2026, including optimizing serving LLMs, RAG and agentic AI.
August 7, 2026
Announcing Capital One's 2026 UIUC AI Awardees
Meet the University of Illinois researchers and fellows advancing Agentic AI through our academic partnership.
Capital One Science | July 8, 2026
LLM reasoning and agentic safety at ICML 2026
Explore our latest research in critique-guided distillation and multi-turn agent uncertainty in Seoul.
Capital One Science | July 1, 2026
Capital One at ACL 2026
Discover how Capital One is advancing state-of-the-art AI/ML science through collaborative natural language processing research.
Capital One Science | June 30, 2026
UVA School of Engineering: Capital One Fellows 2026-2027
Capital One and the University of Virginia celebrate the 2026-2027 engineering fellowship awardees
Capital One Science | June 4, 2026
“We are committed to advancing partnerships between industry, academia, and government to strengthen our national capabilities in AI while ensuring a broad range of expertise and perspectives when developing, testing and deploying cutting-edge AI solutions.”
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