  In this paper, we propose a novel method for the prior-art search task. We
fine-tune SciBERT transformer model using Triplet Network approach, allowing us
to represent each patent with a fixed-size vector. This also enables us to
conduct efficient vector similarity computations to rank patents in query time.
In our experiments, we show that our proposed method outperforms baseline
methods.
