Pranshu Raj

A ~150M-parameter encoder that checks whether a RAG answer is supported by the source it was given. Given an answer and a source (and optionally the question), it returns grounded or hallucinated with P(grounded). It runs on CPU. - Every number below is traceable to a committed report in that repository. Hashes for every file are in the repository's MODELPROVENANCE.json. python -m eval.provenance --verify re-checks them. All measured on CPU against the pinned weights, using test sets rebuilt from pinned public datasets. F1 is for the hallucinated class, and the 95% CIs come from a 2,000-resample bootstrap. - 512 tokens reproduces the training run's published numbers (F1 0.6824, acc 0.7468…