Santiago Valdarrama

There are 4 specialized execution paths here: • Classification • Extraction • Summarization • Context Compression The architecture behind classification and span extraction in their white paper is really cool: They have a task-specific head that reads the input's internal representation and selects a label or source span. This avoids autoregressive token generation for the prediction itself. As a result, classification returns labels from the supplied set. Extraction returns text from the input, along with source offsets and confidence scores. The model can still choose the wrong label or passage, but restricting the answer space makes its outputs easier to validate.