Category

Research

Snorkel AI emerged from a research project, and we remain closely connected to the research community. Students and professors associated with the Snorkel project continue to publish academic papers that push the field forward, and the Snorkel AI research team integrates the most promising of those ideas into our platform.

Our picks

Image for Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
Getting better performance from foundation models (with less data)
August 4, 2023
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Fred Sala
Image for Snorkel AI researchers present 18 papers at NeurIPS 2023
Snorkel AI researchers present 18 papers at NeurIPS 2023
The Snorkel AI team will present 18 research papers and talks at the 2023 Neural Information Processing Systems (NeurIPS) conference from December 10-16. The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. Snorkel AI is proud of its roots in the research community and endeavors to remain at the forefront
October 31, 2023
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Team Snorkel
Image for Long context models in the enterprise: benchmarks and beyond
Long context models in the enterprise: benchmarks and beyond
Snorkel researchers devised a new way to evaluate long context models and address their “lost-in-the-middle” challenges with mediod voting.
June 6, 2024
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Amanda Dsouza

All articles on Research

Training Classifiers With Natural Language Explanations
Machine Learning Whiteboard (MLW) Open-source Series Earlier this year, we started our machine learning whiteboard (MLW) series, an open-invite space to brainstorm ideas and discuss the latest papers, techniques, and workflows in the AI space. We emphasize an informal and open environment to everyone interested in learning about machine learning.In this episode, our Co-founder and Head of Technology. Braden Hancock
May 24, 2021
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Team Snorkel
Applying Information Theory to ML With Fred Sala
In this episode of Science Talks, Frederic Sala – an assistant professor of Computer Science at the University of Wisconsin Madison and a research scientist at Snorkel discusses his path into machine learning, the central thesis that ties together his multidisciplinary research, his thoughts on the future of weak supervision, as well as his decision to go into academia.
May 19, 2021
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Team Snorkel
3 Impractical Assumptions About AI to Avoid
Impractical ML assumptions are made every day in research, which limit its adoption. In the real world, these assumptions do not hold up. Learn more about how to avoid making these assumptions about AI application development.
May 4, 2021
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Braden Hancock
Measuring NLP Progress With Sebastian Ruder
In this episode of Science Talks, Sebastian Ruder, Research Scientist at DeepMind, shares his thoughts on making AI practical with Snorkel AI’s Braden Hancock. This conversation covers progress made in the NLP domain with emerging research, new benchmarks like SuperGLUE, rich repositories and news sources that keep you in the loop and on top of what’s new in NLP, and more.
March 10, 2021
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Team Snorkel
Productionizing ML Research With Thomas Wolf
In this episode of ScienceTalks, Snorkel AI’s Braden Hancock Hugging Face’s Chief Science Officer, Thomas Wolf. Thomas shares his story about how he got into machine learning and discusses important design decisions behind the widely adopted Transformers library, as well as the challenges of bringing research projects into production. ScienceTalks is an interview series from Snorkel AI, highlighting some of the best work and ideas to make AI practical.
February 5, 2021
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Team Snorkel