Education
NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding
By utilizing the technique, we can facilitate training and education, improve quality control, and enable operational compliance monitoring.
Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing Y ongrui Chen
Conventional methods tend to suffer from overfitting with limited supervision, as well as catastrophic forgetting due to parameter updates.
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
Most of the literature on learning in games has focused on the restrictive setting where the underlying repeated game does not change over time.
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
The enhanced model expressivity, however, comes at a great cost of inference complexity.
FedL2P: Federated Learning to Personalize
In this paper, we consider the federated meta-learning problem of learning personalization strategies. Specifically, we consider meta-nets that induce the batch-norm and learning rate parameters for each client given local data statistics.
