Prospero specialized LLM outperforms base model on 250‑question ICF benchmark (arXiv:2610.38024v1)
The paper (arXiv:2610.38024v1) presents an expert‑curated 250‑question benchmark for inertial confinement fusion (ICF) covering qualitative reasoning, numerical calculation, symbolic derivation, and equation formulation, and compares out‑of‑the‑box closed‑ and open‑source LLMs to Prospero, a model specialized via domain‑adaptive pretraining and supervised fine‑tuning. Prospero improved its aggregate score by 10.7 percentage points over its base model; frontier models scored highest overall but still made critical physics and numerical errors, retrieval helped a smaller model but not frontier models, and the authors warn that benchmark gains do not establish scientific reliability.