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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
Image for Why Frontier Agents Fail Real Engineering Work: Two Terminal-Bench 3.0 Task Deep Dives
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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Harvard professor: DataPerf and AI’s need for data benchmarks
Blog
Harvard professor: DataPerf and AI’s need for data benchmarks

Harvard Professor Vijay Janapa Reddi’s presentation: “DataPerf: Benchmarks for data” from Snorkel AI’s 2022 Future of Data-Centric AI event.

Apr 25, 2023 •
Learn more about Harvard professor: DataPerf and AI’s need for data benchmarks
Learning to Compose Soft Prompts for Compositional Zero-Shot Learning
We introduce compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositionality of large-scale pretrained vision-language models (VLMs) like CLIP. We develop CSP for compositional zero-shot learning, the task of predicting unseen attribute-object compositions (e.g., old cat and young tiger). VLMs have a flexible text encoder that can represent arbitrary classes as natural language prompts but they often underperform taskspecific architectures on the compositional zero-shot benchmark datasets. CSP treats the attributes and objects that define classes as learnable tokens of vocabulary. During training, the vocabulary is tuned to recognize classes that compose tokens in multiple ways (e.g.,...
Research Paper
Learning to Compose Soft Prompts for Compositional Zero-Shot Learning

We introduce compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositionality of large-scale pretrained vision-language models (VLMs) like CLIP. We develop CSP for compositional zero-shot learning, the task of predicting unseen attribute-object compositions (e.g., old cat and young tiger). VLMs have a flexible text encoder that can represent arbitrary classes as natural language prompts but they…

Apr 24, 2023 •

N. Nayak et al.

Learn more about Learning to Compose Soft Prompts for Compositional Zero-Shot Learning
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes
A long standing goal of the data management community is to develop general, automated systems that ingest semi-structured documents and output queryable tables without human effort or domain specific customization. Given the sheer variety of potential documents, state-of-the art systems make simplifying assumptions and use domain specific training. In this work, we ask whether we can maintain generality by using large language models (LLMs). LLMs, which are pretrained on broad data, can perform diverse downstream tasks simply conditioned on natural language task descriptions. We propose and evaluate EVAPORATE, a simple, prototype system powered by LLMs. We identify two fundamentally different...
Research Paper
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes

A long standing goal of the data management community is to develop general, automated systems that ingest semi-structured documents and output queryable tables without human effort or domain specific customization. Given the sheer variety of potential documents, state-of-the art systems make simplifying assumptions and use domain specific training. In this work, we ask whether we can maintain generality by using…

Apr 21, 2023 •

S. Arora, et al.

Learn more about Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes
AI for banking in the era of ChatGPT
Blog
AI for banking in the era of ChatGPT

Forward-looking companies in finance, including banks, have looked to technology to meet challenges and are reaping the rewards of doing so.

Apr 20, 2023 •
Learn more about AI for banking in the era of ChatGPT
Uniphore chooses Snorkel Flow to accelerate conversational AI
Blog
Uniphore chooses Snorkel Flow to accelerate conversational AI

Uniphore, a conversational AI and automation leader, has chosen Snorkel’s data-centric AI platform to accelerate AI development.

Apr 19, 2023 •
Learn more about Uniphore chooses Snorkel Flow to accelerate conversational AI
Discovering climate change impact  with Snorkel-enabled NLP
Blog
Discovering climate change impact with Snorkel-enabled NLP

Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022.

Apr 18, 2023 •
Learn more about Discovering climate change impact with Snorkel-enabled NLP
AMA technique: a trick to build systems with foundation models
Blog
AMA technique: a trick to build systems with foundation models

Simran Arora is a machine learning researcher at Stanford University. She presented “Ask Me Anything: How are Foundation Models Changing the Way We Build Software” at Snorkel AI’s Foundation Model Virtual Summit 2023.

Apr 13, 2023 •
Learn more about AMA technique: a trick to build systems with foundation models
Coactive AI’s CEO: quality beats quantity for data selection
Blog
Coactive AI’s CEO: quality beats quantity for data selection

Cody Coleman, CEO and Co-Founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022.

Apr 11, 2023 •
Learn more about Coactive AI’s CEO: quality beats quantity for data selection
Snorkel AI x Hugging Face: unlock foundation models for enterprises
Blog
Snorkel AI x Hugging Face: unlock foundation models for enterprises

Snorkel AI teamed up with Hugging Face to provide enterprises with even more flexibility and choice as they develop AI applications.

Apr 06, 2023 •
Learn more about Snorkel AI x Hugging Face: unlock foundation models for enterprises
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