How Far Back Should a Transformer Look? Repetition and Copying in Music Sequence Models

We investigate how predictive performance depends on the maximum context available to an autoregressive model of symbolic music, and what information long-context models exploit. A small causal Transformer is trained separately at each context length T in {6, 18, 48, 96, 192, 336} and evaluated on t