Item representations in M/MS task

[jexterliangsufe]

Great works.
When I dive into data processing codes for Traffic or Electricity datasets, I find that seq_x length is (seq_len, ), which means multi variates are split to univariate and considered by model seperately.
Then I noticed that the model actually accept (B, T, C) input where C=1, which means the model doesn't know which variate is feeded into.
The question is, have you considered about extracting the item representation and feeding them into a new embedding layer like static embedding layer?

[kwuking]

Thank you very much for your interest in our work. Your understanding is correct. Currently, Time-LLM adopts a channel-independent approach and does not consider the interactions between multivariate variables. The use of a static embedding layer you mentioned is indeed a very interesting method. We have also explored this approach. However, there is a small issue that we have not yet been able to solve adequately: how to handle unseen time series during inference, as new time series are not included in the original static encoding. This is something that may require further thought.