Transformer-DIA is an extension of the DeepNovo-DIA architecture that replaces the convolutional layers in the spectrum encoder with transformer self-attention layers. After extracting the same precursor profile and theoretical product ion array for each precursor feature as DeepNovo-DIA, the model encodes the temporal information of successive MS2 scans using a positional embedding, allowing the LSTM decoding to be replaced by a standard transformer decoder layer. Additionally, Transformer-DIA includes a beam search decoding procedure similar to the one employed by Casanovo.