resources

Resource library

Explore our complete library of resources including blogs, benchmarks, research papers and more.
Image for Evaluating coding agent capabilities with Terminal-Bench: Snorkel’s role in building the next generation benchmark
Blog

Evaluating coding agent capabilities with Terminal-Bench: Snorkel’s role in building the next generation benchmark

Announcing a $3M commitment to launch Open Benchmarks Grants
September 30, 2025
Image for Closing the Evaluation Gap in Agentic AI
Blog

Closing the Evaluation Gap in Agentic AI

Announcing a $3M commitment to launch Open Benchmarks Grants

February 11, 2026
Image for Benchtalks #1: Alex Shaw (Terminal-Bench, Harbor) – Building the Benchmark Factory
Blog

Benchtalks #1: Alex Shaw (Terminal-Bench, Harbor) – Building the Benchmark Factory

Announcing a $3M commitment to launch Open Benchmarks Grants
March 31, 2026
Image for Building FinQA: An Open RL Environment for Financial Reasoning Agents
Blog

Building FinQA: An Open RL Environment for Financial Reasoning Agents

Announcing a $3M commitment to launch Open Benchmarks Grants
March 30, 2026
Image for The science of rubric design
Blog

The science of rubric design

Announcing a $3M commitment to launch Open Benchmarks Grants
September 11, 2025
of
Type: All Types
Sort: Newest
Swellshark: A Generative Model for Biomedical Named Entity Recognition Without Labeled Data
Introducing SwellShark, a framework for building biomedical named entity recognition (NER) systems quickly.
Research Paper
Swellshark: A Generative Model for Biomedical Named Entity Recognition Without Labeled Data

Introducing SwellShark, a framework for building biomedical named entity recognition (NER) systems quickly.

Nov 13, 2017
J. Fries, et al, 2017
Learn more about Swellshark: A Generative Model for Biomedical Named Entity Recognition Without Labeled Data
Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data
Introducing Socratic learning, a paradigm that uses feedback from a discriminative model to automatically identify latent data subsets in training data.
Research Paper
Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data

Introducing Socratic learning, a paradigm that uses feedback from a discriminative model to automatically identify latent data subsets in training data.

Nov 13, 2017
P. Varma, et al, 2017
Learn more about Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data
Snorkel: Rapid Training Data Creation With Weak Supervision
Research Paper
Snorkel: Rapid Training Data Creation With Weak Supervision

This paper presents a flexible interface layer to write labeling functions based on experience.

Oct 04, 2017
Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, Christopher Ré
Learn more about Snorkel: Rapid Training Data Creation With Weak Supervision
Data Programming: Creating Large Training Sets, Quickly
Research Paper
Data Programming: Creating Large Training Sets, Quickly

A paradigm for labeling training datasets programmatically rather than by hand.

Dec 20, 2016
A. Ratner, et al. 2016
Learn more about Data Programming: Creating Large Training Sets, Quickly
Data Programming With DDLite: Putting Humans in a Different Part of the Loop
Research Paper
Data Programming With DDLite: Putting Humans in a Different Part of the Loop

Introducing DDLite, an interactive development framework for data programming.

Dec 19, 2016
H. Ehrenberg, et al, 2016
Learn more about Data Programming With DDLite: Putting Humans in a Different Part of the Loop
1 2 63 64
Image

Join our newsletter

For expert advice, the latest research, and exclusive events.

By submitting this form, I acknowledge I will receive email updates from Snorkel AI, and I agree to the Terms of Use and acknowledge that my information will be used in accordance with the Privacy Policy.