Multi-Head Classification Model
A model architecture that attaches multiple independent classification output layers on top of a shared encoder, with each head responsible for predicting one subtask or dimension. In evaluation scenarios, a single forward pass yields multi-dimensional scores. It has few parameters, low inference cost, and stable, reproducible outputs.
Timeline (last 90 days)
A multi-classification-head model attaches multiple independent classification output layers on top of a shared encoder, with each head responsible for a subtask or one dimension of prediction.
The author plans to expand the experiment and obtain annotation data for a small multiple-heads classification model.
All Facts (2)
A multi-classification-head model attaches multiple independent classification output layers on top of a shared encoder, with each head responsible for a subtask or one dimension of prediction.
50%UnverifiedThe author plans to expand the experiment and obtain annotation data for a small multiple-heads classification model.
50%