IPO Finance Agent benchmarks LLMs on SpaceX S-1 questions with contextual retrieval and auto-generated rubrics, reporting up to 79.8% accuracy and better cost-efficiency than prior Finance Agent v2 entries.
YC Bench: a Live Benchmark for Forecasting Startup Outperformance in Y Combinator Batches
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abstract
Forecasting startup success is notoriously difficult, partly because meaningful outcomes, such as exits, large funding rounds, and sustained revenue growth, are rare and can take years to materialize. As a result, signals are sparse and evaluation cycles are slow. Y Combinator batches offer a unique mitigation: each batch comprises around 200 startups, funded simultaneously, with evaluation at Demo Day only three months later. We introduce YC Bench, a live benchmark for forecasting early outperformance within YC batches. Using the YC W26 batch as a case study (196 startups), we measure outperformance with a Pre-Demo Day Score, a KPI combining publicly available traction signals and web visibility. This short-term metric enables rapid evaluation of forecasting models. As a baseline, we take Google mentions prior to the YC W26 application deadline, a simple proxy for prior brand recognition, recovering 6 of 11 top performers at YC Demo Day (55% recall). YC Bench provides a live benchmark for studying startup success forecasting, with iteration cycles measured in months rather than years. Code and Data are available on GitHub: https://github.com/benstaf/ycbench
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
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IPO Finance Agent: Benchmark of LLM Financial Analysts Beyond Finance Agent v2, with Automated Rubric Generation, on the SpaceX (SPCX) IPO
IPO Finance Agent benchmarks LLMs on SpaceX S-1 questions with contextual retrieval and auto-generated rubrics, reporting up to 79.8% accuracy and better cost-efficiency than prior Finance Agent v2 entries.