Education
A Potential Negative Societal Impacts
In addition, users may become overly dependent on the model's outputs For the feedback, we ask the person "Please consider the quality of the Given a score (1-5). 1 means its quality is bad, and 5 means its quality is very good". The interface of the user study is shown in Fig. A1. We report the average scores in Tab. We have a total of 1.1M training data in FIRE. In Fig. A2, we present the curves of A T, A TR, A TR, and RR using different Results show that more data leads to better performance.
OpenDlign: Open-World Point Cloud Understanding with Depth-Aligned Images
Moreover, the volume discrepancy between 3D and 2D pretraining datasets highlights the need for effective strategies to transfer the representational abilities of VLMs to 3D learning.
Responsible AI (RAI) Games and Ensembles
In this work, we provide a general framework for studying these problems, which we refer to as Responsible AI (RAI) games .
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
However, due to the heterogeneity between the clients' data distributions, the model obtained through the use of FL algorithms may perform poorly on some client's data.
Adaptive Proximal Gradient Method for Convex Optimization
In this paper, we explore two fundamental first-order algorithms in convex optimization, namely, gradient descent (GD) and proximal gradient method (ProxGD). Our focus is on making these algorithms entirely adaptive by leveraging local curvature information of smooth functions.
Bias in Evaluation Processes: An Optimization-Based Model L. Elisa Celis Y ale University Amit Kumar IIT Delhi Anay Mehrotra Y ale University Nisheeth K. Vishnoi Y ale University
In these processes, an evaluator estimates an individual's value to an institution.