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Found 4 papers, 2 papers with code
Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning
While there are many definitions of fairness that could be applicable in the context of personalized systems, we present a framework which we call the Variance Reduction System (VRS) for achieving more equitable outcomes in Meta's ads systems.
CoRTX: Contrastive Framework for Real-time Explanation
In this work, we propose a COntrastive Real-Time eXplanation (CoRTX) framework to learn the explanation-oriented representation and relieve the intensive dependence of explainer training on explanation labels.
Accelerating Shapley Explanation via Contributive Cooperator Selection
Even though Shapley value provides an effective explanation for a DNN model prediction, the computation relies on the enumeration of all possible input feature coalitions, which leads to the exponentially growing complexity.
A Web Scale Entity Extraction System
Understanding the semantic meaning of content on the web through the lens of entities and concepts has many practical advantages.
