Agentic data science with the Data Agent Kit
cloud.google.com·7h ago
AI Research
arXiv CS.AI·28d ago·5 min read
WinSyn: An Automated Pipeline for Realistic Enterprise Question-Answering Evaluation
TL;DR
WinSyn is an automated pipeline that generates synthetic datasets for evaluating question-answering systems in enterprise environments. It highlights the challenges of real-world data, revealing that current models score below 80% on complex queries.
✦ Why It Matters
Consider integrating WinSyn-generated datasets to better evaluate your enterprise question-answering models today.
Key Takeaways
- Utilize WinSyn for realistic dataset generation in evaluations.
- Focus on long-form questions to challenge your models.
- Assess model performance against complex, real-world scenarios.
- Prioritize improvements based on evaluation results below 80%.
How It Works
WinSyn generates synthetic datasets by simulating long-term enterprise projects, incorporating interactions among multiple employees. It creates realistic scenarios that reflect the ambiguity and distributed nature of information in workplace communications.