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Explore our complete library of resources including blogs, benchmarks, research papers, and more.

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Blog

Data 2.0 and the research era of AI data

Announcing Snorkel’s $350M fundraise to build the frontier lab for AI data.

September 22, 2026
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Blog

Terminal-Bench 4.0: Why Continuous Benchmarks Require Continuous QA

Announcing a $3M commitment to launch Open Benchmarks Grants
August 28, 2026
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Blog

Grok 4.5 Testing Results: How SpaceXAI’s New Model Performs on Real Professional Work

Announcing a $3M commitment to launch Open Benchmarks Grants
July 8, 2026
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Blog

Why coding agents need better data, evals, and environments

Announcing a $3M commitment to launch Open Benchmarks Grants
May 11, 2026
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Blog

Closing the Evaluation Gap in Agentic AI

Announcing a $3M commitment to launch Open Benchmarks Grants

February 11, 2026
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Blog

Why Frontier Agents Fail Real Engineering Work: Two Terminal-Bench 3.0 Task Deep Dives

Announcing a $3M commitment to launch Open Benchmarks Grants
August 24, 2026
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Blog

Building FinQA: An Open RL Environment for Financial Reasoning Agents

Announcing a $3M commitment to launch Open Benchmarks Grants
March 30, 2026
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Blog

The science of rubric design

Announcing a $3M commitment to launch Open Benchmarks Grants
September 11, 2025
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Blog

Benchtalks #3: We taught AI everything except how to learn

Featuring Parth Asawa (Continual Learning Bench)

June 25, 2026
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LLM distillation techniques to explode in importance in 2024
Blog
LLM distillation techniques to explode in importance in 2024

LLM distillation will become a more important in 2024, according to a poll of attendees at Snorkel AI’s 2023 Enterprise LLM virtual summit.

Nov 09, 2023 •
Learn more about LLM distillation techniques to explode in importance in 2024
Weak Supervision Enables Scalable Post-Market Surveillance on Medical Wearables
Introduction: With the advent of consumer-facing devices that can render atrial fibrillation (AF) pre-diagnosis, medical wearables now have the potential to affect diagnosis rates and medical care. Post-market surveillance is necessary to understand the impact of wearables on patient outcomes and health care utilization, but is hindered by the lack of codified terms in EHR that capture wearable use. Research Questions: Constructing a post-market surveillance system therefore requires a classifier that identifies mentions of AF pre-diagnosis in unstructured EHR data. However, fine-tuning classifiers require large, hand-labeled training sets that can be costly to generate. It is unclear whether a scalable...
Research Paper
Weak Supervision Enables Scalable Post-Market Surveillance on Medical Wearables

Introduction: With the advent of consumer-facing devices that can render atrial fibrillation (AF) pre-diagnosis, medical wearables now have the potential to affect diagnosis rates and medical care. Post-market surveillance is necessary to understand the impact of wearables on patient outcomes and health care utilization, but is hindered by the lack of codified terms in EHR that capture wearable use. Research…

Nov 06, 2023 •

RM. Yoo, et al.

Learn more about Weak Supervision Enables Scalable Post-Market Surveillance on Medical Wearables
How to fine-tune large language models for enterprise use cases
Blog
How to fine-tune large language models for enterprise use cases

LLMs have a broad but shallow knowledge, but fall short on specialized tasks. For best performance, enterprises must fine tune their LLMs.

Nov 02, 2023 •
Learn more about How to fine-tune large language models for enterprise use cases
Snorkel Flow 2023.R3 release: PaLM integration, streamlined onboarding, and enhanced user experience
Blog
Snorkel Flow 2023.R3 release: PaLM integration, streamlined onboarding, and enhanced user experience

The 2023.R3 Snorkel Flow release is packed with improvements that amplify user experience, streamline workflows, and enhance performance, ensuring our users derive unparalleled value from our platform.

Nov 01, 2023 •
Learn more about Snorkel Flow 2023.R3 release: PaLM integration, streamlined onboarding, and enhanced user experience
Navigating Biden’s AI executive order with AI data development
Blog
Navigating Biden’s AI executive order with AI data development

The Biden administration issued an executive order that creates new AI standards and challenges. AI data development can help.

Oct 31, 2023 •
Learn more about Navigating Biden’s AI executive order with AI data development
Snorkel AI researchers present 18 papers at NeurIPS 2023
Blog
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…

Oct 31, 2023 •
Learn more about Snorkel AI researchers present 18 papers at NeurIPS 2023
Two approaches to distill LLMs for better enterprise value
Blog
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.

Oct 31, 2023 •
Learn more about Two approaches to distill LLMs for better enterprise value
Enterprise LLM Summit highlights the importance of data development
Blog
Enterprise LLM Summit highlights the importance of data development

Snorkel AI’s Enterprise LLM Virtual Summit drew 1,000 attendees with speakers from Contextual AI, Google, Meta, Stanford, and Together AI.

Oct 27, 2023 •
Learn more about Enterprise LLM Summit highlights the importance of data development
Zero-Shot Robustification of Zero-Shot Models with Foundation Models
Zero-shot inference is a powerful paradigm that enables the use of large pretrained models for downstream classification tasks without further training. However, these models are vulnerable to inherited biases that can impact their performance. The traditional solution is fine-tuning, but this undermines the key advantage of pretrained models, which is their ability to be used out-of-the-box. We propose ROBOSHOT, a method that improves the robustness of pretrained model embeddings in a fully zero-shot fashion. First, we use zero-shot language models (LMs) to obtain useful insights from task descriptions. These insights are embedded and used to remove harmful and boost useful...
Research Paper
Zero-Shot Robustification of Zero-Shot Models with Foundation Models

Zero-shot inference is a powerful paradigm that enables the use of large pretrained models for downstream classification tasks without further training. However, these models are vulnerable to inherited biases that can impact their performance. The traditional solution is fine-tuning, but this undermines the key advantage of pretrained models, which is their ability to be used out-of-the-box. We propose ROBOSHOT, a…

Oct 20, 2023 •

D. Adila, et al.

Learn more about Zero-Shot Robustification of Zero-Shot Models with Foundation Models
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