Jamie Kiros
Also known as Jamie Ryan Kiros
Jamie Kiros is a machine-learning researcher whose papers cover layer normalization, visual-semantic embeddings, insertion-based sequence generation, and synthetic text for NLP. Layer Normalization, a 2016 paper written with Jimmy Lei Ba and Geoffrey Hinton, computes the mean and variance from all of the summed inputs to the neurons in a layer. He also co-wrote a 2020 study of generation order for machine translation that builds on insertion-based modeling. He was listed among the authors of OpenAI's GPT-4o System Card in 2024.
- Works
- 25
- Citations
- 1,859
- h-index
- 13
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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2016
Layer normalization
He co-writes Layer Normalization with Jimmy Lei Ba and Geoffrey Hinton in 2016, a method that computes the mean and variance from all of the summed inputs to the neurons in a layer.
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2017
VSE++ with hard negatives
In 2017 he co-writes VSE++ with Fartash Faghri, David Fleet, and Sanja Fidler, a method that improves visual-semantic embeddings with hard negatives.
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2019
The Insertion Transformer
He co-writes the Insertion Transformer with Mitchell Stern, William Chan, and Jakob Uszkoreit in 2019, a model for sequence generation based on insertion operations.
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2020
Generation order in translation
A 2020 study of generation order for machine translation, co-written with William Chan, Mitchell Stern, and Jakob Uszkoreit, builds on insertion-based modeling.
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2021
Synthetic text for NLP
He co-writes Generate, Annotate, and Learn: NLP with Synthetic Text with Xuanli He, Islam Nassar, Gholamreza Haffari, and Mohammad Norouzi, a 2021 preprint on language models as a source of synthetic text.
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2024
Author on the GPT-4o system card
He appears among the authors of OpenAI's GPT-4o System Card in 2024.
Sources and credits
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- [1607.06450] Layer Normalization
- [1707.05612] VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
- [1902.03249] Insertion Transformer: Flexible Sequence Generation via Insertion Operations
- Insertion Transformer: Flexible Sequence Generation via Insertion Operations
- An Empirical Study of Generation Order for Machine Translation - ACL Anthology
- [2106.06168] Generate, Annotate, and Learn: NLP with Synthetic Text
- GPT-4o System Card