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cs.AI2026★ 2 cited
CIRCLE: A Framework for Evaluating AI from a Real-World Lens
Reva Schwartz, Carina Westling, Morgan Briggs +12
This paper proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI's materialized outcomes in deployment.…
cs.AI2025
Intrinsic Bias is Predicted by Pretraining Data and Correlates with Downstream Performance in Vision-Language Encoders
Kshitish Ghate, Isaac Slaughter, Kyra Wilson +2
While recent work has found that vision-language models trained under the Contrastive Language Image Pre-training (CLIP) framework contain intrinsic social biases, the extent to wh…