[Quizzical4230]

All benefits depend on the ability of the embedding model. Semantic embeddings understand nuances, so they can match abstracts that align conceptually even if no exact keywords overlap. For example, "neural networks" vs. "deep learning." can and should fetch similar papers.

Subjectively, yes. I sent this around my peers and they said it helped them find new authors/papers in the field while preparing their manuscripts.

| Is this more useful in certain domains?

I don't think I have the capacity to comment on this.