Uploaded August 2026 | Updated September 2026, 1 week ago
At our inaugural YCML at Startup School, YC Partner Ankit Gupta speaks with MIT PhD candidate Jovana Kondic about ChartNet, an open-source data generation pipeline and million-scale dataset for chart understanding.
Charts require models to combine visual recognition, text understanding, and numerical reasoning. ChartNet generates diverse examples by translating charts into plotting code, augmenting that code, and rendering new images with corresponding tables, summaries, and reasoning traces. Training on ChartNet improved open-source models across a range of chart tasks and transferred to real-world benchmarks, showing how carefully structured synthetic data can give smaller models capabilities commonly associated with much larger systems.
Apply to Y Combinator: ycombinator.com/apply
Work at a startup: ycombinator.com/jobs
At our inaugural YCML at Startup School, YC Partner Ankit Gupta speaks with MIT PhD candidate Jovana Kondic about ChartNet, an open-source data generation pipeline and million-scale dataset for chart understanding.
Charts require models to combine visual recognition, text understanding, and numerical reasoning. ChartNet generates diverse examples by translating charts into plotting code, augmenting that code, and rendering new images with corresponding tables, summaries, and reasoning traces. Training on ChartNet improved open-source models across a range of chart tasks and transferred to real-world benchmarks, showing how carefully structured synthetic data can give smaller models capabilities commonly associated with much larger systems.
Apply to Y Combinator: ycombinator.com/apply
Work at a startup: ycombinator.com/jobs
