Avik Pal

PhD
ELLIS Institute Tübingen
Bosch Center for Artificial Intelligence (BCAI)
Foundation Models for Improving and Auditing Data at Scale

The goal of this project is to develop novel and automated data auditing methods, leveraging foundation models. These methods shall enable data analysis at scale, provide insights into models' generalization capabilities and aid performance estimation in new domains. Additionally, outcomes from data auditing will be utilized to improve data quality, e.g., pruning less relevant samples, adding more valuable ones, and generating advanced annotations to expedite learning with smaller models and model evaluation.

Track:
Industry Track
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