Government
Multi-Group Proportional Representation in Retrieval
Current approaches to mitigate these representational harms balance the number of retrieved items across population groups defined by a small number of (often binary) attributes. However, most existing methods overlook intersectional groups determined by combinations of group attributes, such as gender, race, and ethnicity.
Value Imprint: AT echnique for Auditing the Human Values Embedded in RLHF Datasets
Our analysis involved a two-phase process.
Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
Deep neural networks (DNNs) have showcased their remarkable precision in approximating smooth functions.
cdf6f8e9fd9aeaf79b6024caec24f15b-Paper-Datasets_and_Benchmarks_Track.pdf
To ensure quality, all charts and questions are handpicked, curated, and verified by human experts.
Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context
When making decisions under uncertainty, individuals often deviate from rational behavior, which can be evaluated across three dimensions: risk preference, probability weighting, and loss aversion.
Matching the Statistical Query Lower Bound for k-Sparse Parity Problems with Sign Stochastic Gradient Descent
's in this subset is even or odd.
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
However, enabling human trust and control over FL systems requires understanding the evolving behaviour of clients, whether beneficial or detrimental for the training, which still represents a key challenge in the current literature.
