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

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Research spotlight: Is intent analysis the key to unlocking more accurate LLM question answering?
Learn how ARR improves QA accuracy in LLMs through intent analysis, retrieval, and reasoning. Is intent the key to smarter AI? Explore ARR results!
February 27, 2025
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Shane Johnson
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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
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How ROBOSHOT boosts zero-shot foundation model performance
ROBOSHOT acts like a lens on foundation models and improves their zero-shot performance without additional fine-tuning.
April 30, 2024
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Dyah Adila
Snorkel teams with Microsoft to showcase new AI research at NVIDIA image
Snorkel teams with Microsoft to showcase new AI research at NVIDIA GTC
Microsoft infrastructure facilitates Snorkel AI research experiments, including our recent high rank on the AlpacaEval 2.0 LLM leaderboard.
March 18, 2024
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Snorkel Team
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How Skill-it! enables faster, better LLM training
Humans learn tasks better when taught in a logical order. So do LLMs. Researchers developed a way to exploit this tendency called “Skill-it!”
March 12, 2024
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Fred Sala
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Large language model training: three phases that shape LLM training
Training large language models is a multi-layered stack of processes, each with its unique role and contribution to the model’s performance.
February 27, 2024
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Stephen Bach
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LoRA: Low-Rank Adaptation for LLMs
Low-rank adaptation (LoRA) lets data scientists customize GenAI models like LLMs faster than traditional full fine-tuning methods.
February 21, 2024
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Matt Casey
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New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
Snorkel researchers’ state-of-the-art methods created a 7B LLM that ranked 2nd, behind only GPT-4 Turbo, on AlpacaEval 2.0 leaderboard.
January 24, 2024
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Cate Lochead
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Retrieval augmented generation (RAG): a conversation with its creator
Snorkel CEO Alex Ratner spoke with Douwe Keila, an author of the original paper about retrieval augmented generation (RAG).
January 16, 2024
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Team Snorkel
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Stanford professor discusses exciting advances in foundation model evaluation
Snorkel CEO Alex Ratner chatted with Stanford Professor Percy Liang about evaluation in machine learning and in AI generally.
January 2, 2024
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Team Snorkel
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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
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Two approaches to distill LLMs for better enterprise value
Distillation techniques allow enterprises to access the full predictive power of large language models at a tiny fraction of their cost.
October 31, 2023
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Jason Fries
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Bloomberg’s Gideon Mann on the power of domain specialist LLMs
Gideon Mann, head of ML Product and Research at Bloomberg LP, chatted with Snorkel CEO Alex Ratner about building BloombergGPT.
October 17, 2023
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Team Snorkel
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Which is better, retrieval augmentation (RAG) or fine-tuning? Both.
Professionals in the data science space often debate whether RAG or fine-tuning yields the better result. The answer is “both.”
September 20, 2023
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Hoang Tran
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Former U.S. Chief Data Scientist on past and future of data science
Past U.S. Chief Data Scientist DJ Patil talked with Snorkel AI CEO Alex Ratner on topics including the origin of the title “data scientist.”
September 12, 2023
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Team Snorkel