Vincent Sunn Chen

For our third Benchtalks, the series dedicated to the researchers building the measurement toolkits that frontier labs hill-climb on, Snorkel AI co-founder Vincent Sunn Chen sat down with Parth Asawa, a PhD student at UC Berkeley advised by Matei Zaharia and Joey Gonzalez. Parth leads research on continual learning and is the creator of Continual Learning Bench, developed in collaboration…

For our second Benchtalks, the series dedicated to the researchers building the measurement toolkits that frontier labs hill-climb on, Snorkel AI co-founder Vincent Sunn Chen sat down with John Yang, a Stanford PhD student and creator of the SWE-bench franchise, SWE-smith, CodeClash, and most recently ProgramBench. Highlights More on ProgramBench: See the benchmark and the upcoming leaderboard at programbench.com. More from John Yang: Publications and writing at john-b-yang.github.io. Snorkel…

Since launching the Open Benchmarks Grants, we’ve received more than 100 applications from academic groups and industry labs spanning a wide range of domains and capabilities. As the best benchmarks have driven how the field allocates research effort, the bar for what counts as useful has risen. Here, we share what’s now table stakes for useful benchmarks, and what separates…

To kick off our inaugural Benchtalks, a series dedicated to the researchers building these measurement toolkits, Snorkel AI co-founder Vincent Sunn Chen sat down with Alex Shaw, Founding MTS at Laude Institute and co-creator of Terminal-Bench and Harbor. Highlights More on Terminal-Bench: See the leaderboard and the catalog of tasks at tbench.ai. Explore Harbor: Learn how to scale your agent…

Announcing a $3M commitment to launch Open Benchmarks Grants Today, AI is marked by a growing asymmetry: the excitement around agentic AI is real—backed by quantitative progress on model cards and genuine leaps forward, especially in coding. But ask individuals or enterprises where they feel ready to deploy agentic automation in high-stakes, domain-specific settings outside of coding… and you will…

Enterprises must evaluate LLM performance for production deployment. Custom, automated eval + data slices present the best path to production.

When done right, advanced classification applications cultivate business value and automation, unlock new business lines, and reduce costs.

Enabling iterative development workflows with Snorkel Flow’s Application Studio. Consider this scenario— we’re AI engineers, and we’re building a social media monitoring application to track the sentiment of Fortune 500 company mentions in the news.

Proposing Slice-based Learning, a new programming model in which the slicing function (SF), a programmer abstraction, is used to specify additional model capacity for each slice.