Research

On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

Trend · papers per month

count % of corpus

1 result for “Symptom-to-Diagnosis”

Uncertainty Quantification of Large Language Models using Approximate Bayesian Computationcs.LG

ABC improves uncertainty quantification in LLMs for clinical diagnostics.

problem Overconfident and poorly calibrated estimates of LLMs in clinical domains.

method Approximate Bayesian Computation (ABC) for likelihood-free inference.

result Improves accuracy by up to 46.9%, reduces Brier scores by 74.4%, and enhances calibration.

Large Language Models Uncertainty Quantification Bayesian Inference Clinical Diagnostics Symptom-to-Diagnosis

2025-09-19abs ↗pdf ↗