Genre
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts
In particular, it aggregates multiple sub-models called experts based on a gating network. Here, experts can be formulated as neural networks, and they specialize in different aspects of the data.
Treeffuser: Probabilistic Predictions via Conditional Diffusions with Gradient-Boosted Trees Nicolas Beltran-V elez
Probabilistic prediction aims to compute predictive distributions rather than single point predictions. These distributions enable practitioners to quantify uncertainty, compute risk, and detect outliers. However, most probabilistic methods assume parametric responses, such as Gaussian or Poisson distributions.
Large Language Model Unlearning via Embedding-Corrupted Prompts
Instead of relying on the LLM itself to unlearn, we enforce an unlearned state during inference by employing a prompt classifier to identify and safeguard prompts to forget.
Exploring Embodied Emotion Through A Large-Scale Egocentric Video Dataset Wang Lin
We employ a total of 26 annotators, consisting of 14 females and 12 males.
Data Acquisition via Experimental Design for Data Markets Charles Lu
The acquisition of training data is crucial for machine learning applications.
