I tried bert and bart to output embedding of document and query.
Bart is much better than bert ,.
However in zero-shot learning condition, the embedding of sentence looks good when they have similar length, but when using embedding of query which is really short, the embedding is much worse. The embedding  of query is much closer to  the short rubbish data other than the long relative data.
Are there good models or training tasks to map query and document into a similar space which has no relation with the length of sentences?