---
title: "Jimmy Lei Ba — author profile and papers — Elamur Research"
description: "Jimmy Lei Ba: 6 papers on Elamur Research (2014–2023), h-index 34 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/jimmy-lei-ba/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jimmy-lei-ba/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Jimmy Lei Ba

# Jimmy Lei Ba

Jimmy Lei Ba has 6 papers in our library, in 2014–2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Keiran Paster](https://md.research.elamur.ai/free/en/authors/keiran-paster/), [Aaron Courville](https://md.research.elamur.ai/free/en/authors/aaron-courville/), [Carlos Guestrin](https://md.research.elamur.ai/free/en/authors/carlos-guestrin/).

6 papers in our library · 2014–2023

[OpenAlex](https://openalex.org/A5012276327) · [ORCID](https://orcid.org/0009-0000-9062-4180) · [Wikidata](https://www.wikidata.org/wiki/Q130802831) · [**h-index 34**](https://openalex.org/authors/A5012276327) · [92 works](https://openalex.org/works?filter=author.id:A5012276327) · [93,626 citations](https://openalex.org/works?filter=author.id:A5012276327&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/#papers) · [🔗 Cited 15,364 times in our library](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/cited-by/) · [70 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #4](https://md.research.elamur.ai/free/en/paper-stars/#star-4)

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

## Affiliations

[🎓**University of Toronto** Toronto · Canada 2013–2025 · 50 papers](https://md.research.elamur.ai/free/en/universities/university-of-toronto/) · [🔬**Vector Institute** Toronto · Canada 2023–2024 · 3 papers](https://md.research.elamur.ai/free/en/labs/vector-institute/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Decision Sciences · 2 works](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Management Science and Operations Research · 2 works](https://md.research.elamur.ai/free/en/shelves/decision-sciences/management-science-and-operations-research/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Mathematics · 2 works](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Numerical Analysis · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/numerical-analysis/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/)

🧭 Topics 3 Research subjects and languages the work is about.[Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

💡 Concepts 1 Key ideas and methods explained on our concept pages.[Machine learning · 1 work](https://md.research.elamur.ai/free/en/concepts/machine-learning/)

## Works by year

### 2020s

[**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/year/2023/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/year/2022/)

### 2010s

[**2016** 1 paper](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/year/2016/) · [**2015** 1 paper](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/year/2015/) · [**2014** 1 paper](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/year/2014/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Adam: A Method for Stochastic Optimization](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)** *(2014 · 90,277 citations)* Training large models on noisy, minibatch-based objectives needs a first-order optimizer that is cheap, light on memory, and robust to gradient scale, sparse gradients and objectives that drift over time.
2. **[Show, Attend and Tell: Neural Image Caption Generation with Visual Attention](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)** *(2015 · 7,670 citations)* The paper tackles automatic image captioning: producing a natural-language sentence that describes a photo.
3. **[Layer Normalization](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)** *(2016 · 1,819 citations)* Batch normalization speeds up training of deep networks, but it estimates its statistics from the mini-batch.
4. **[Large Language Models Are Human-Level Prompt Engineers](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/)** *(2022 · 701 citations)* How well a large language model does a task depends heavily on the wording of its instruction, and good prompts are usually written by hand through trial and error.
5. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/)** *(2023 · 456 citations)* Training instruction-following LLMs with human feedback is costly and slow to iterate on. It is also hard to evaluate reliably, and commercial vendors document it poorly. AlpacaFarm is a sandbox for cheaply studying learning from pairwise feedback (LPF). It has three parts:
6. **[OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)** *(2023 · 132 citations)* Large language models get noticeably better at quantitative reasoning when trained on math-heavy text. Minerva showed this, but its web corpus was never released. Existing open web datasets also mangle mathematical notation during HTML-to-text conversion, so open researchers had no comparable resource. The authors…

## All works

76 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them.

1. [**Adam: A Method for Stochastic Optimization arXiv:1412.6980**Diederik P. Kingma, Jimmy Ba*2014 · 90,277 citations*](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)
2. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention arXiv:1502.03044**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,670 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
3. [**Layer Normalization arXiv:1607.06450**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
4. **[Do Deep Nets Really Need to be Deep? ↗](https://arxiv.org/abs/1312.6184) arXiv (Cornell University) · no summary yet**Jimmy Lei Ba, Rich Caruana*2013 · 1,496 citations*
5. [**Large Language Models Are Human-Level Prompt Engineers arXiv:2211.01910**Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.*2022 · 701 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/)
6. **[Multiple Object Recognition with Visual Attention ↗](https://arxiv.org/abs/1412.7755) arXiv (Cornell University) · no summary yet**Jimmy Lei Ba, Volodymyr Mnih, Koray Kavukcuoglu*2014 · 698 citations*
7. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 456 citations*
8. **[Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation ↗](https://arxiv.org/abs/1708.05144) arXiv (Cornell University) · no summary yet**Yuhuai Wu et al.*2017 · 450 citations*
9. **[Classifying and segmenting microscopy images with deep multiple instance learning ↗](https://doi.org/10.1093/bioinformatics/btw252) Bioinformatics · no summary yet**Oren Z. Kraus, Jimmy Lei Ba, Brendan J. Frey*2016 · 416 citations*
10. **[Lookahead Optimizer: k steps forward, 1 step back ↗](https://arxiv.org/abs/1907.08610) arXiv (Cornell University) · no summary yet**Michael R. Zhang et al.*2019 · 380 citations*
11. **[Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions ↗](https://doi.org/10.1109/iccv.2015.483) IEEE International Conference on Computer Vision (ICCV) · no summary yet**Jimmy Lei Ba et al.*2015 · 361 citations*
12. **[Adaptive dropout for training deep neural networks ↗](https://openalex.org/W2136836265) neural information processing systems · no summary yet**Jimmy Lei Ba, Brendan J. Frey*2013 · 272 citations*
13. **[Dream to Control: Learning Behaviors by Latent Imagination ↗](https://arxiv.org/abs/1912.01603) arXiv:1912.01603 · no summary yet**Danijar Hafner et al.*2019 · 228 citations*
14. **[Benchmarking Model-Based Reinforcement Learning ↗](https://arxiv.org/abs/1907.02057) arXiv (Cornell University) · no summary yet**Tingwu Wang et al.*2019 · 223 citations*
15. **[Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning ↗](https://arxiv.org/abs/1511.06342) arXiv (Cornell University) · no summary yet**Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov*2015 · 217 citations*
16. **[Mastering diverse control tasks through world models ↗](https://doi.org/10.1038/s41586-025-08744-2) Nature · no summary yet**Danijar Hafner et al.*2025 · 200 citations*
17. **[Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches ↗](https://arxiv.org/abs/1803.04386) arXiv:1803.04386 · no summary yet**Yeming Wen et al.*2018 · 189 citations*
18. **[Mastering Diverse Domains through World Models ↗](https://arxiv.org/abs/2301.04104) arXiv:2301.04104 · no summary yet**Danijar Hafner et al.*2023 · 182 citations*
19. **[Using Fast Weights to Attend to the Recent Past ↗](https://arxiv.org/abs/1610.06258) arXiv (Cornell University) · no summary yet**Jimmy Lei Ba et al.*2016 · 168 citations*
20. **[NerveNet: Learning Structured Policy with Graph Neural Networks ↗](https://openalex.org/W2785948534) International Conference on Learning Representations · no summary yet**Tingwu Wang et al.*2018 · 148 citations*
21. [**OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text arXiv:2310.06786**Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)
22. **[The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning ↗](https://arxiv.org/abs/2403.03218) arXiv:2403.03218 · no summary yet**Nathaniel Li et al.*2024 · 127 citations*
23. **[BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning ↗](https://arxiv.org/abs/2002.06715) arXiv (Cornell University) · no summary yet**Yeming Wen, Dustin Tran, Jimmy Lei Ba*2020 · 108 citations*
24. **[Identifying the Risks of LM Agents with an LM-Emulated Sandbox ↗](https://arxiv.org/abs/2309.15817) arXiv:2309.15817 · no summary yet**Yangjun Ruan et al.*2023 · 96 citations*
25. **[Mastering Atari with Discrete World Models ↗](https://arxiv.org/abs/2010.02193) arXiv:2010.02193 · no summary yet**Danijar Hafner et al.*2020 · 92 citations*

[See all 76 works by Jimmy Lei Ba →](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/works/)

## Co-authors here

12 of 20 co-authors with a page, the most papers together first.

- [Keiran Paster](https://md.research.elamur.ai/free/en/authors/keiran-paster/) ×2
- [Aaron Courville](https://md.research.elamur.ai/free/en/authors/aaron-courville/)
- [Carlos Guestrin](https://md.research.elamur.ai/free/en/authors/carlos-guestrin/)
- [Diederik P. Kingma](https://md.research.elamur.ai/free/en/authors/diederik-p-kingma/)
- [Geoffrey E. Hinton](https://md.research.elamur.ai/free/en/authors/geoffrey-e-hinton/)
- [Ishaan Gulrajani](https://md.research.elamur.ai/free/en/authors/ishaan-gulrajani/)
- [Jamie Kiros](https://md.research.elamur.ai/free/en/authors/jamie-kiros/)
- [Kelvin Xu](https://md.research.elamur.ai/free/en/authors/kelvin-xu/)
- [Kyunghyun Cho](https://md.research.elamur.ai/free/en/authors/kyunghyun-cho/)
- [Marco Dos Santos](https://md.research.elamur.ai/free/en/authors/marco-dos-santos/)
- [Percy Liang](https://md.research.elamur.ai/free/en/authors/percy-liang/)
- [Richard S. Zemel](https://md.research.elamur.ai/free/en/authors/richard-s-zemel/)

## Venues

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

- International Conference on Learning Representations ×4
- neural information processing systems ×4
- [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2023](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/)
- Bioinformatics
- Communications in computer and information science
- Findings of the Association for Computational Linguistics: ACL 2023
- IEEE International Conference on Computer Vision (ICCV)
- International Conference on Artificial Intelligence and Statistics
- International Conference on Machine Learning
- Nature
- Uncertainty in Artificial Intelligence

## Cited by

Papers of our library cite their works 15,364 times (of the 149,439 papers whose bibliographies we read); [1,475 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/cited-by/).

Updated 30 October 2026