SciMuse generates personalized research ideas from a 58-million-paper knowledge graph and an LLM; over 100 research group leaders rated 4,400+ ideas at a mean of 2.40 on a 5-point scale, with 24.9% rated 4 or 5
The authors introduce SciMuse, which generates personalized research ideas using a knowledge graph of 58 million papers and a large language model, and they conducted a large-scale evaluation in which more than 100 research group leaders spanning the natural sciences to the humanities rated over 4,400 personalized ideas by level of interest; expert ratings were modest (mean 2.40 on a 5-point scale, most common rating 1) while 24.9% of ideas were rated 4 or 5, supplying knowledge-graph-selected concept pairs did not improve expert-rated interest over a titles-only GPT baseline, high-citation-predicted pairs even showed a weak tendency (1.