Category
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
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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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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All articles on Research
Research spotlight: is long chain-of-thought structure all that matters when it comes to LLM reasoning distillation?
We’re taking a look at the research paper, LLMs can easily learn to reason from demonstration (Li et al., 2025), in this week’s community research spotlight. It focuses on how the structure of reasoning traces impacts distillation from models such as DeepSeek R1. What’s the big idea regarding LLM reasoning distillation? The reasoning capabilities of powerful models such as DeepSeek
March 19, 2025
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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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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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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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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
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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Large language model training: how three training phases shape LLMs
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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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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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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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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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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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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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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