Nina Fatehi

Clinical dialogue-to-note generation is high-volume and intolerant of fabrication; a 4B-parameter model inside a fixed four-evaluator verification stack comes close to a frontier model on factual entailment, with its deficit concentrated in inter-section structure. Treating verifier rejection as an escalation signal reaches 99.6% end-to-end acceptance against 98.4% for frontier-only, statistically indistinguishable, while three quarters of encounters need no frontier generation call.

Clinical dialogue-to-note generation is high-volume and intolerant of fabrication; a 4B-parameter model inside a fixed four-evaluator verification stack comes close to a frontier model on factual entailment, with its deficit concentrated in inter-section structure. Treating verifier rejection as an escalation signal reaches 99.6% end-to-end acceptance against 98.4% for frontier-only, statistically indistinguishable, while three quarters of encounters need no frontier generation call.